{ "count" : 152334, "data" : [ { "id" : "6a30794df292fd229c031216", "title" : "Director, Data and AI Engineering", "company" : "Benevity", "industry" : "Technology", "salary" : { "min" : 192000.0, "max" : 238810.0, "currency" : "CAD", "frequency" : "Yearly" }, "location" : "Toronto, Ontario", "locations" : [ "Toronto, Ontario" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T15:07:30.375", "fingerprint" : "aaf0e33227ca131481be4962d98f3d416a3d9e7ac0a72837e11beccb51a05d5d", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/benevity/791ccf38-f164-4521-b05d-6f35fa1e7245/application", "externalId" : "791ccf38-f164-4521-b05d-6f35fa1e7245", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.6534817,-79.3839347" } ], "locationText" : "Toronto, Ontario, Canada", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "Python, SQL, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio, Kubernetes, Terraform, Kafka, Flink, Apache Beam, Lambda, Kinesis, Pub/Sub", "professionalSkills" : [ "Data strategy", "Data modeling", "Business intelligence", "Data governance", "ML systems engineering", "Product intelligence", "AI-powered services", "Data-driven decision-making", "Scalable data engineering", "AI/ML systems", "Cloud-based data architectures", "Real-time analytics", "ML/AI-driven solutions", "Client needs", "Data-as-a-product", "Data assets", "Real-time analytics", "AI-powered automation", "Data-driven insights", "Self-service analytics", "Data pipelines", "Enterprise warehousing", "ML training", "Business reporting", "AI-powered features", "Anomaly detection", "Personalization", "Cost optimization", "MLOps", "CI/CD", "Real-time inference", "Recommendations", "Predictive analytics", "NLP", "Generative AI", "Ethical AI", "AI standards", "BI tools", "Dashboards", "Product analytics", "User behavior", "Feature engagement", "Embedded analytics", "SaaS metrics", "Data privacy", "Data security", "Compliance", "Data lineage", "Metadata management", "MDM", "RBAC", "ABAC", "ReBac", "Data sharing", "Data democratization", "Trusted data", "Documented data", "Team leadership", "Budget management", "Product innovations", "Multi-tenant SaaS", "Customer-facing analytics", "Emerging AI trends", "Responsible AI frameworks" ], "hardSkillsList" : [ "Regression", "Classification", "Clustering", "Time-series", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data Engineering, AI/ML Engineering, Data Strategy, Business Intelligence", "majorSkillsList" : [ "Data Engineering", "AI/ML Engineering", "Data Strategy", "Business Intelligence" ], "coreResponsibilities" : "Define and execute data and AI strategy, Lead cross-functional teams, Establish data-as-a-product principles, Drive innovation in real-time analytics, Partner with Product, Engineering, and Customer Success teams, Design and oversee high-scale, cloud-native data architectures, Implement highly available, fault-tolerant data pipelines, Lead data modeling initiatives, Work with engineering teams to embed AI-powered features, Drive observability, monitoring, and cost optimization, Oversee the development of ML/AI models, Implement MLOps best practices, Lead initiatives in AI-powered recommendations, Ensure bias-free, ethical AI practices, Build and manage BI tools, Develop product analytics frameworks, Implement embedded analytics solutions, Optimize reporting for SaaS metrics, Own data governance frameworks, Define and implement data lineage, Drive role-based access controls, Champion data democratization", "teamCollaboration" : "Cross-functional teams; Product teams; Engineering teams; Customer Success teams", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "B2B SaaS; Cloud-native architecture; Multi-tenant SaaS; SaaS metrics; GDPR; SOC 2; PIPEDA; CCPA", "domainList" : [ "b2b-saas", "cloud-native-architecture", "multi-tenant-saas", "saas-metrics", "gdpr", "soc-2", "pipeda", "ccpa" ], "domainSpecificKnowledge" : [ "B2B SaaS", "Cloud-native architecture", "Multi-tenant SaaS", "SaaS metrics", "GDPR", "SOC 2", "PIPEDA", "CCPA" ], "toolProficiency" : [ "Collibra", "Informatica", "Alation", "Immuta", "JIRA" ], "communicationSkills" : "Executive presentations; Technical documentation", "documentationSkills" : "Technical writing; API documentation; Architecture diagrams", "continuousLearning" : "Growth opportunities", "innovationCreativity" : "Innovation", "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "qualificationsBasic" : "10+ years of experience in data engineering, AI/ML, or analytics leadership roles, SQL proficiency, Master's or PhD in", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "MEET BENEVITY Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more! We are seeking a Director of Data and ML/AI Engineering to lead our data and AI technology strategy, architecture, and execution within our B2B SaaS Benevity Impact Platform. This role is pivotal in enabling data-driven decision-making, product intelligence, and AI-powered services and automation across our platform. The ideal candidate will have deep expertise in scalable data engineering, AI/ML systems and services, and cloud-based data architectures, with a track record of building highly available, real-time analytics, and ML/AI-driven solutions for SaaS platforms. This role will oversee data science, data modeling, business intelligence, governance, and ML/AI systems engineering, ensuring alignment with our client and business needs. What you’ll do: Leadership & Data Strategy - Define and execute the data and AI strategy for our SaaS platform, ensuring alignment with business objectives and customer needs. - Lead cross-functional teams across data engineering, AI/ML, BI, and governance to deliver scalable, high-impact solutions. - Establish data-as-a-product principles, ensuring data assets are secure, reusable, and monetizable within our platform. - Drive innovation in real-time analytics, AI-powered automation and intelligence for clients. - Partner with Product, Engineering, and Customer Success teams to enhance data-driven insights, reporting, and self-service analytics. Data Engineering & Platform Architecture - Design and oversee high-scale, cloud-native data architectures that support real-time streaming, data lakes / lakehouses, and enterprise warehousing. - Implement highly available, fault-tolerant data pipelines to process, store, and serve insights across the platform. - Lead data modeling initiatives to optimize data structures for analytics, ML training, and business reporting. - Work with engineering teams to embed AI-powered features into the SaaS platform, enabling smart automation, anomaly detection, and personalization. - Drive observability, monitoring, and cost optimization across our cloud-based data infrastructure. AI/ML Engineering & Data Science - Oversee the development of ML/AI models, ensuring they are scalable, explainable, and deployed effectively in production. - Implement MLOps best practices, including CI/CD for models, versioning, and real-time inference. - Lead initiatives in AI-powered recommendations, predictive analytics, NLP, and generative AI to enhance our product offerings. - Ensure bias-free, ethical AI practices and compliance with industry AI standards and regulations. Business Intelligence & Product Analytics - Build and manage BI tools, dashboards, and self-service analytics to provide real-time insights to clients and internal stakeholders. - Develop product analytics frameworks, tracking user behavior, adoption, and feature engagement. - Implement embedded analytics solutions that allow clients to gain actionable insights from their data. - Optimize reporting for SaaS metrics (MRR, ARR, churn, retention, LTV, NPS) and drive data-informed decision-making. Data Governance & Compliance - Own data governance frameworks, ensuring data privacy, security, and compliance (GDPR, SOC 2, PIPEDA, CCPA, etc.). - Define and implement data lineage, metadata management, and master data management (MDM) best practices. - Drive role-based access controls (RBAC, ABAC or ReBac) and ensure secure, auditable data sharing within our SaaS ecosystem. - Champion data democratization, enabling teams to access trusted, well-documented data. What you’ll bring: - 10+ years of experience in data engineering, AI/ML, or analytics leadership roles, ideally in B2B SaaS or cloud-based platforms - Strong expertise in scalable data architectures, ML/AI systems, and embedded analytics - Proven track record in leading high-performance teams, managing budgets, and delivering data-driven product innovations - Experience with multi-tenant SaaS data governance, compliance (SOC 2, GDPR, etc.), and customer-facing analytics - Familiarity with emerging AI trends, including LLMs, Generative AI, and responsible AI frameworks - Familiarity with SaaS product analytics and AI-powered automation use cases - Master’s or PhD in Computer Science, Data Science, AI/ML, or a related field is preferred Technical Skills & Expertise - Data & AI Stacks (Cloud-Native, SaaS-Optimized) - Data Engineering & Storage: BigQuery, Redshift, Delta Lake, Snowflake, Databricks - AI/ML Frameworks: Azure AI, TensorFlow, PyTorch, Hugging Face, MLflow, Vertex AI - MLOps & Pipelines: Kubeflow, SageMaker, Airflow, Feature Stores, DataRobot - BI & Analytics Tools: Looker, Power BI, Mode Analytics, Amplitude, Mixpanel - Data Governance & Security: Collibra, Informatica, Alation, Immuta - Cloud & DevOps: AWS (S3, Lambda, Kinesis), GCP (BigQuery, Pub/Sub), Kubernetes, Terraform - Programming: Python, SQL, Scala, Java - Streaming & Real-Time Data: Kafka, Flink, Apache Beam DISCOVER YOUR PURPOSE AT WORK We’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more … Innovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose. If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become … It’s time to join Benevity. We’re so excited to meet you. WHERE WE WORK At Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most. JOIN A COMPANY WHERE DEIB ISN’T A BUZZWORD Diversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily — from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams. We know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine. That starts with a fair and accessible hiring process. If you want to feel seen, heard and celebrated, you belong at Benevity. Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to accommodations@benevity.com.", "summaryDescription" : "Director, Data and AI Engineering at Benevity. Skills: Data Engineering, AI/ML Engineering, Data Strategy, Business Intelligence. Define and execute data and AI strategy. Lead cross-functional teams", "createdAt" : "2026-06-16T01:59:44.833", "lastUpdated" : "2026-06-16T15:07:30.375", "ingestTimestamp" : "2026-06-16T01:59:44.833", "mongoId" : "6a30794df292fd229c031216", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Regression", "Classification", "Clustering", "Time-series", "A/B testing", "Causal inference", "Leadership", "Data Engineering", "AI/ML Engineering", "Data Strategy", "Business Intelligence", "Data strategy", "Data modeling", "Business intelligence", "Data governance", "ML systems engineering", "Product intelligence", "AI-powered services", "Data-driven decision-making", "Scalable data engineering", "AI/ML systems", "Cloud-based data architectures", "Real-time analytics", "ML/AI-driven solutions", "Client needs", "Data-as-a-product", "Data assets", "AI-powered automation", "Data-driven insights", "Self-service analytics", "Data pipelines", "Enterprise warehousing", "ML training", "Business reporting", "AI-powered features", "Anomaly detection", "Personalization", "Cost optimization", "MLOps", "CI/CD", "Real-time inference", "Recommendations", "Predictive analytics", "NLP", "Generative AI", "Ethical AI", "AI standards", "BI tools", "Dashboards", "Product analytics", "User behavior", "Feature engagement", "Embedded analytics", "SaaS metrics", "Data privacy", "Data security", "Compliance", "Data lineage", "Metadata management", "MDM", "RBAC", "ABAC", "ReBac", "Data sharing", "Data democratization", "Trusted data", "Documented data", "Team leadership", "Budget management", "Product innovations", "Multi-tenant SaaS", "Customer-facing analytics", "Emerging AI trends", "Responsible AI frameworks", "Agile", "B2B SaaS", "Cloud-native architecture", "GDPR", "SOC 2", "PIPEDA", "CCPA", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Collibra", "Informatica", "Alation", "Immuta", "JIRA" ], "skillCount" : 90, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3074d9f292fd229c009d20", "title" : "Director, Data and AI Engineering", "company" : "Benevity", "industry" : "Technology", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data for Director, Data and AI Engineering in Calgary, Canada, adjusted for SaaS industry and company size." }, "location" : "Calgary, Alberta", "locations" : [ "Calgary, Alberta", "Vancouver, British Columbia" ], "timestamp" : "2026-06-16T11:55:49.932", "fingerprint" : "48d6e9e7d6092e824c8f4e626ef408c40aef8877a09c5443b28ff1eaf3b039e9", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/benevity/863fc534-814d-4aed-a969-d52dd5e43dc2/application", "externalId" : "863fc534-814d-4aed-a969-d52dd5e43dc2", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Calgary", "state" : "Alberta", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "51.0456064,-114.0575410" } ], "locationText" : "Calgary, Alberta, Canada", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "remoteFriendly" : true, "rawDescription" : "MEET BENEVITY Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more! We are seeking a Director of Data and ML/AI Engineering to lead our data and AI technology strategy, architecture, and execution within our B2B SaaS Benevity Impact Platform. This role is pivotal in enabling data-driven decision-making, product intelligence, and AI-powered services and automation across our platform. The ideal candidate will have deep expertise in scalable data engineering, AI/ML systems and services, and cloud-based data architectures, with a track record of building highly available, real-time analytics, and ML/AI-driven solutions for SaaS platforms. This role will oversee data science, data modeling, business intelligence, governance, and ML/AI systems engineering, ensuring alignment with our client and business needs. What you’ll do: Leadership & Data Strategy - Define and execute the data and AI strategy for our SaaS platform, ensuring alignment with business objectives and customer needs. - Lead cross-functional teams across data engineering, AI/ML, BI, and governance to deliver scalable, high-impact solutions. - Establish data-as-a-product principles, ensuring data assets are secure, reusable, and monetizable within our platform. - Drive innovation in real-time analytics, AI-powered automation and intelligence for clients. - Partner with Product, Engineering, and Customer Success teams to enhance data-driven insights, reporting, and self-service analytics. Data Engineering & Platform Architecture - Design and oversee high-scale, cloud-native data architectures that support real-time streaming, data lakes / lakehouses, and enterprise warehousing. - Implement highly available, fault-tolerant data pipelines to process, store, and serve insights across the platform. - Lead data modeling initiatives to optimize data structures for analytics, ML training, and business reporting. - Work with engineering teams to embed AI-powered features into the SaaS platform, enabling smart automation, anomaly detection, and personalization. - Drive observability, monitoring, and cost optimization across our cloud-based data infrastructure. AI/ML Engineering & Data Science - Oversee the development of ML/AI models, ensuring they are scalable, explainable, and deployed effectively in production. - Implement MLOps best practices, including CI/CD for models, versioning, and real-time inference. - Lead initiatives in AI-powered recommendations, predictive analytics, NLP, and generative AI to enhance our product offerings. - Ensure bias-free, ethical AI practices and compliance with industry AI standards and regulations. Business Intelligence & Product Analytics - Build and manage BI tools, dashboards, and self-service analytics to provide real-time insights to clients and internal stakeholders. - Develop product analytics frameworks, tracking user behavior, adoption, and feature engagement. - Implement embedded analytics solutions that allow clients to gain actionable insights from their data. - Optimize reporting for SaaS metrics (MRR, ARR, churn, retention, LTV, NPS) and drive data-informed decision-making. Data Governance & Compliance - Own data governance frameworks, ensuring data privacy, security, and compliance (GDPR, SOC 2, PIPEDA, CCPA, etc.). - Define and implement data lineage, metadata management, and master data management (MDM) best practices. - Drive role-based access controls (RBAC, ABAC or ReBac) and ensure secure, auditable data sharing within our SaaS ecosystem. - Champion data democratization, enabling teams to access trusted, well-documented data. What you’ll bring: - 10+ years of experience in data engineering, AI/ML, or analytics leadership roles, ideally in B2B SaaS or cloud-based platforms - Strong expertise in scalable data architectures, ML/AI systems, and embedded analytics - Proven track record in leading high-performance teams, managing budgets, and delivering data-driven product innovations - Experience with multi-tenant SaaS data governance, compliance (SOC 2, GDPR, etc.), and customer-facing analytics - Familiarity with emerging AI trends, including LLMs, Generative AI, and responsible AI frameworks - Familiarity with SaaS product analytics and AI-powered automation use cases - Master’s or PhD in Computer Science, Data Science, AI/ML, or a related field is preferred Technical Skills & Expertise - Data & AI Stacks (Cloud-Native, SaaS-Optimized) - Data Engineering & Storage: BigQuery, Redshift, Delta Lake, Snowflake, Databricks - AI/ML Frameworks: Azure AI, TensorFlow, PyTorch, Hugging Face, MLflow, Vertex AI - MLOps & Pipelines: Kubeflow, SageMaker, Airflow, Feature Stores, DataRobot - BI & Analytics Tools: Looker, Power BI, Mode Analytics, Amplitude, Mixpanel - Data Governance & Security: Collibra, Informatica, Alation, Immuta - Cloud & DevOps: AWS (S3, Lambda, Kinesis), GCP (BigQuery, Pub/Sub), Kubernetes, Terraform - Programming: Python, SQL, Scala, Java - Streaming & Real-Time Data: Kafka, Flink, Apache Beam DISCOVER YOUR PURPOSE AT WORK We’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more … Innovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose. If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become … It’s time to join Benevity. We’re so excited to meet you. WHERE WE WORK At Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most. JOIN A COMPANY WHERE DEIB ISN’T A BUZZWORD Diversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily — from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams. We know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine. That starts with a fair and accessible hiring process. If you want to feel seen, heard and celebrated, you belong at Benevity. Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to accommodations@benevity.com.", "summaryDescription" : "Director, Data and AI Engineering at Benevity", "createdAt" : "2026-06-16T00:25:36.052", "lastUpdated" : "2026-06-16T11:55:49.932", "ingestTimestamp" : "2026-06-16T00:25:36.052", "mongoId" : "6a3074d9f292fd229c009d20", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3075c5f292fd229c013566", "title" : "Software Engineer, Customer Insights", "company" : "Pantheon Systems, Inc", "industry" : "SaaS", "salary" : { "min" : 116640.0, "max" : 145800.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Remote", "locations" : [ "Remote" ], "timestamp" : "2026-06-16T13:27:53.744", "fingerprint" : "f4a8f719538a36fe57f0ba3367ed03ca78b403947c3149dae93677fb8e623bb4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://pantheon.io/about/careers/detail?gh_jid=8008383", "externalId" : "8008383", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Python, Java, Go, JavaScript, React, Node.js, SQL, NoSQL, AWS, GCP, Azure, Kubernetes, Docker, Terraform, CI/CD, REST, GraphQL", "professionalSkills" : [ "System design", "API design", "Data modeling" ], "hardSkillsList" : [ "Software development", "Cloud computing", "DevOps practices", "Data structures", "Algorithms" ], "hardSkills" : [ { "name" : "Software development", "level" : "intermediate" }, { "name" : "Cloud computing", "level" : "intermediate" }, { "name" : "DevOps practices", "level" : "intermediate" }, { "name" : "Data structures", "level" : "intermediate" }, { "name" : "Algorithms", "level" : "intermediate" } ], "majorSkills" : "Backend development, Cloud infrastructure, DevOps", "majorSkillsList" : [ "Backend development", "Cloud infrastructure", "DevOps" ], "coreResponsibilities" : "Design scalable backend services, Develop and maintain cloud infrastructure, Implement CI/CD pipelines, Write clean, maintainable code, Collaborate with cross-functional teams, Troubleshoot and resolve production issues, Participate in code reviews, Contribute to system architecture discussions", "teamCollaboration" : "Cross-functional teams; Agile methodologies; Code reviews", "projectManagementSkills" : [ "Agile", "Scrum" ], "domainKnowledge" : "SaaS architecture; Customer insights; Data pipelines", "domainList" : [ "saas-architecture", "customer-insights", "data-pipelines" ], "domainSpecificKnowledge" : [ "SaaS architecture", "Customer insights", "Data pipelines" ], "toolProficiency" : [ "Git", "JIRA", "Datadog", "Prometheus", "Grafana" ], "documentationSkills" : "Technical documentation", "continuousLearning" : "Professional development", "problemSolvingSkills" : "Troubleshooting; Root cause analysis", "qualificationsBasic" : "3+ years experience", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Pantheon Pantheon brings together exceptional builders who take ownership, drive meaningful impact, and shape what's next for the web. We power more than 300,000 websites globally for organizations including Google, Princeton, Salesloft, Clorox, and the United Nations. Every day, thousands of developers and marketers use our WebOps platform to build, iterate, and scale WordPress, Drupal, and Next.js sites that reach billions of people worldwide. As an employer, we operate with the same philosophy that drives our product: foundation and freedom. Pantheon is a vibrant, remote-forward team of experts who care deeply about their craft and results. Here, you take ownership of work that matters, contribute alongside exceptional people, and see the impact you create. The Role The Pantheon Customer Insights Team is looking for a Software Engineer to build the next generation of customer-facing observability features. In this role, you will create backend systems that transform raw observability data from platforms like New Relic, Grafana, and Cloudflare into clear, actionable insights surfaced directly in our product. You'll work on Portfolio Insights, OpenTelemetry exploration, and product analytics capabilities. This is product engineering work; you're building features customers interact with daily, not internal tooling. You will work primarily in Go, with Python and SQL for data work. What you Need to Succeed Comfort with ambiguity; you'll be defining what \"meaningful insights\" means to customers. Pragmatic approach to balancing performance, cost, and delivery speed. Care about what users see, not just APIs. Good collaboration skills to work with product, design, and cross-functional teams. Desire to learn observability concepts on the job (we have domain experts on the team to teach you). What you Bring to the Table 3+ years of experience building production services and features. Go experience is a plus (or similar systems language). Comfortable working in React and TypeScript and GraphQL. Comfort with BigQuery/SQL and with Python for data work. Experience with observability platforms (New Relic, Grafana, Datadog) Experience with RESTful APIs and distributed systems. What We Offer We have all the usual perks and benefits but what we can really offer you is a fantastic work environment powered by an amazing team. Industry competitive compensation and equity plan Flexible time off, sick days, and 13 paid holidays Comprehensive medical insurance including Health, Dental and Vision Paid parental leave (plus fertility, adoption and other family planning benefits) In-office workspace (San Francisco & Chicago) Monthly allowance for wellness, reading and access to LinkedIn Learning for continued development Events and activities both team-based and company wide that inspire, educate and cultivate Pantheon is an equal opportunity employer and we welcome applications from all backgrounds regardless of race, color, religion, sex, national origin, ancestry, age, marital status, sexual orientation, gender identity, veteran status, disability, or any other classification protected by law. Pantheon complies with federal and local disability laws and makes reasonable accommodations for applicants and employees with disabilities. If you need a reasonable accommodation due to a disability for any part of the interview process, please contact talent@pantheon.io. Pursuant to local and federal regulations, Pantheon will consider qualified applicants with arrest and conviction records for employment. After an offer is made and accepted, E-verify will be utilized to establish your identity and employment eligibility as required by the U. S. Department of Homeland Security. To review the Employee and Applicant's Privacy Policy, click here. The US base salary range for this position in the United States is $116,640 - $145,800 USD per year. Our salary ranges are determined by role, level, and location. At Pantheon, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. Visa Sponsorship is not available at this time. #LI-KM1 #LI-remote", "summaryDescription" : "Software Engineer, Customer Insights at Pantheon Systems, Inc. Skills: Backend development, Cloud infrastructure, DevOps. Design scalable backend services. Develop and maintain cloud infrastructure", "postedDate" : "2026-06-16T01:16:53.432", "createdAt" : "2026-06-16T01:16:53.432", "lastUpdated" : "2026-06-16T13:27:53.744", "ingestTimestamp" : "2026-06-16T01:16:53.432", "mongoId" : "6a3075c5f292fd229c013566", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 116640, "salaryAnnualMax" : 145800, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Software development", "Cloud computing", "DevOps practices", "Data structures", "Algorithms", "Backend development", "Cloud infrastructure", "DevOps", "System design", "API design", "Data modeling", "Agile", "Scrum", "SaaS architecture", "Customer insights", "Data pipelines", "Git", "JIRA", "Datadog", "Prometheus", "Grafana" ], "skillCount" : 21, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3075c5f292fd229c013564", "title" : "Software Engineer - Customer Insights", "company" : "Pantheon Systems, Inc", "industry" : "Technology", "salary" : { "min" : 103000.0, "max" : 129000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Remote", "locations" : [ "Remote" ], "timestamp" : "2026-06-16T11:26:50.191", "fingerprint" : "19157624d10a98ed4b1b9b172e121868012fcbe4130660a9f3eb0319a8a2a186", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://pantheon.io/about/careers/detail?gh_jid=8008258", "externalId" : "8008258", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Pantheon Pantheon WebOps Platform powers the open web, running more than 300,000 sites in the cloud for customers including Google, Princeton, Salesloft and Doctors Without Borders. Every day, thousands of developers and marketers create, iterate, and scale WordPress and Drupal sites to reach billions of people globally. Pantheon’s multitenant, container-based platform enables organizations to manage all of their websites from a single dashboard. Organizations including Clorox and the United Nations drive results through accelerated development and real-time publishing using Pantheon’s collaborative workflows. The Role The Pantheon Customer Insights Team is looking for a Software Engineer to build the next generation of customer-facing observability features. In this role, you will create backend systems that transform raw observability data from platforms like New Relic, Grafana, and Cloudflare into clear, actionable insights surfaced directly in our product. You'll work on Portfolio Insights, OpenTelemetry exploration, and product analytics capabilities. This is product engineering work; you're building features customers interact with daily, not internal tooling. You will work primarily in Go, with Python and SQL for data work. What you Need to Succeed Comfort with ambiguity; you'll be defining what \"meaningful insights\" means to customers. Pragmatic approach to balancing performance, cost, and delivery speed. Care about what users see, not just APIs. Good collaboration skills to work with product, design, and cross-functional teams. Desire to learn observability concepts on the job (we have domain experts on the team to teach you). What you Bring to the Table 3+ years of experience building production services and features. Go experience is a plus (or similar systems language). Comfortable working in React and TypeScript and GraphQL. Comfort with BigQuery/SQL and with Python for data work. Experience with observability platforms (New Relic, Grafana, Datadog) Experience with RESTful APIs and distributed systems. Familiarity with GCP infrastructure primitives, terraform, and container management solutions like kubernetes What We Offer We have all the usual perks and benefits but what we can really offer you is a fantastic work environment powered by an amazing team. Industry competitive compensation and equity plan Paid Time Off (PTO), Paid Sick Leave (PSL) and 12 Paid Company Holidays Full medical coverage (Extended health care, dental, vision) Top-of-line equipment In-office workspace (Vancouver, BC Canada) Monthly allowance for wellness, reading and access to LinkedIn Learning for continued development Events and activities both team-based and company wide that inspire, educate and cultivate Pantheon is an equal opportunity employer and we welcome applications from all backgrounds regardless of race, color, religion, sex, national origin, ancestry, age, marital status, sexual orientation, gender identity, veteran status, disability, or any other classification protected by law. Pantheon complies with federal and local disability laws and makes reasonable accommodations for applicants and employees with disabilities. If you need a reasonable accommodation due to a disability for any part of the interview process, please contact talent@pantheon.io. Pursuant to local and federal regulations, Pantheon will consider qualified applicants with arrest and conviction records for employment. To review the Employee and Applicant's Privacy Policy, click here. Visa Sponsorship is not available at this time. The Canadian base salary range for this position is 103,000- 129,000 CAD per year. Our salary ranges are determined by role, level, and location. At Pantheon, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. #LI-KM1 #LI-remote", "summaryDescription" : "Software Engineer - Customer Insights at Pantheon Systems, Inc", "postedDate" : "2026-06-16T01:19:19.388", "createdAt" : "2026-06-16T01:19:19.388", "lastUpdated" : "2026-06-16T11:26:50.191", "ingestTimestamp" : "2026-06-16T01:19:19.388", "mongoId" : "6a3075c5f292fd229c013564", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.97 }, { "id" : "6a306b15f292fd229cfcf414", "title" : "Director Engineering, AI & Data", "company" : "Deloitte", "industry" : "Accounting", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for Director Engineering, AI & Data in Amsterdam, Netherlands, adjusted for seniority and industry." }, "location" : "Amsterdam, NH, Netherlands", "locations" : [ "Amsterdam", "NH", "Netherlands" ], "timestamp" : "2026-06-16T09:38:52.329", "fingerprint" : "3365d362df5ad7a5cac324b9142e16a94b0cb3401a7e31e13cf646345a6bb1b2", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/DeloitteNetherlands/744000132220185-director-engineering-ai-data-consumer-", "externalId" : "744000132220185", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Amsterdam", "state" : "North Holland", "country" : "Netherlands", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.3730796,4.8924534" } ], "locationText" : "Amsterdam, North Holland, Netherlands", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "AWS, Azure, Microservices, Serverless, Kubernetes, Databricks, Snowflake, Real-time data streaming, MLOps, LLMs, Prompt engineering, Responsible AI, APIs, Event-driven architecture, API management, CI/CD, Infrastructure as code, Observability, Agentic Engineering", "professionalSkills" : [ "Strategic vision", "Commercial drive", "Technical architecture", "Value propositions", "Client relationships", "Business development", "Programme delivery", "P&L responsibility" ], "hardSkillsList" : [ "Data transformation", "AI transformation", "Cloud transformation", "Data platforms", "Enterprise data platforms", "Emerging technologies", "Engineering blueprints", "Roadmaps", "Project lifecycle management", "Technology domain", "Multidisciplinary teams", "Development teams", "Generative AI", "Advanced analytics", "AI orchestration", "Platform engineering" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "AI transformation", "level" : "intermediate" }, { "name" : "Cloud transformation", "level" : "intermediate" }, { "name" : "Data platforms", "level" : "intermediate" }, { "name" : "Enterprise data platforms", "level" : "intermediate" }, { "name" : "Emerging technologies", "level" : "intermediate" }, { "name" : "Engineering blueprints", "level" : "intermediate" }, { "name" : "Roadmaps", "level" : "intermediate" }, { "name" : "Project lifecycle management", "level" : "intermediate" }, { "name" : "Technology domain", "level" : "intermediate" }, { "name" : "Multidisciplinary teams", "level" : "intermediate" }, { "name" : "Development teams", "level" : "intermediate" }, { "name" : "Generative AI", "level" : "intermediate" }, { "name" : "Advanced analytics", "level" : "intermediate" }, { "name" : "AI orchestration", "level" : "intermediate" }, { "name" : "Platform engineering", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Engineering, AI, Data, Cloud, Transformation", "majorSkillsList" : [ "Engineering", "AI", "Data", "Cloud", "Transformation" ], "coreResponsibilities" : "Lead strategic and commercial growth, Build and maintain CIO relationships, Build and maintain Chief Architect relationships, Identify and shape opportunities, Define proposals, Convert proposals into engagements, Co-create technical architecture, Guide development teams in implementation, Deliver transformation programmes, Guide clients in developing Engineering blueprints, Guide clients in developing roadmaps, Manage full project lifecycle, Contribute to thought leadership, Inspire multidisciplinary engineering teams, Inspire multidisciplinary development teams, Coach multidisciplinary engineering teams, Coach multidisciplinary development teams, Develop multidisciplinary engineering teams, Develop multidisciplinary development teams, Shape strategy, Drive business development, Deliver complex transformation programmes, Own client relationships, Translate sector challenges into roadmaps, Take responsibility for P&L, Take responsibility for proposals, Take responsibility for programme delivery, Build multidisciplinary teams, Mentor multidisciplinary teams, Forge partnerships with providers, Ensure solutions meet governance standards, Ensure solutions meet privacy standards, Ensure solutions meet ethical standards, Represent practice through thought leadership, Represent practice through industry engagement, Turn insight into business outcomes, Reshape customer experience, Reshape operations, Reshape monetisation", "teamCollaboration" : "Multidisciplinary teams; Diverse stakeholders", "projectManagementSkills" : [ "Project lifecycle management", "Programme delivery" ], "domainKnowledge" : "Consumer Goods; Retail; Travel; Services; Hospitality; Cloud-native architectures; Microservices; Serverless; Kubernetes; Data and AI platforms; Real-time data streaming; MLOps; Generative AI; Advanced analytics; Integration; APIs; Event-driven architecture; API management; DevOps; Platform engineering; Agentic Engineering; Responsible AI", "domainList" : [ "consumer-goods", "retail", "travel", "services", "hospitality", "cloud-native-architectures", "microservices", "serverless", "kubernetes", "data-and-ai-platforms", "real-time-data-streaming", "mlops", "generative-ai", "advanced-analytics", "integration", "apis", "event-driven-architecture", "api-management", "devops", "platform-engineering", "agentic-engineering", "responsible-ai" ], "domainSpecificKnowledge" : [ "Consumer Goods", "Retail", "Travel", "Services", "Hospitality", "Cloud-native architectures", "Microservices", "Serverless", "Kubernetes", "Data and AI platforms", "Real-time data streaming", "MLOps", "Generative AI", "Advanced analytics", "Integration", "APIs", "Event-driven architecture", "API management", "DevOps", "Platform engineering", "Agentic Engineering", "Responsible AI" ], "toolProficiency" : [ "Databricks", "Snowflake" ], "communicationSkills" : "Clear insights; Inspiring teams; Aligning stakeholders; Thought leadership; Industry engagement", "problemSolvingSkills" : "Simplify complex topics", "outcomesObjectives" : "Impactful engagements; Measurable business outcomes", "qualificationsBasic" : "10+ years experience, Shaping and delivering large-scale Engineering, Cloud, AI and Data transformation programmes end-to-end, Advising senior executives, Simplifying complex technical topics", "qualificationsPreferred" : "Chief lead architect or head of an IT department experience, Trusted advisor to C-level and C-1 stakeholders, Strategic partner", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Accelerate our growth in the Consumer (Consumer Goods and Retail) sector and contribute through your strategic vision, commercial drive and deep expertise in Engineering, AI and data-driven transformation. At Deloitte. * Lead strategic and commercial growth of Engineering and Data offerings within the Consumer, Retail and Travel/services/hospitality industry * Build and maintain strong CIO and Chief Architect relationships * Identify and shape opportunities, define proposals, and convert them into impactful engagements * Co-create technical architecture and guide development teams in implementation * Deliver transformation programmes focused on enterprise data platforms, AI, cloud, and emerging technologies * Guide clients in developing Engineering blueprints and roadmaps * Manage the full project lifecycle, from early visioning to implementation and adoption * Contribute to Deloitte’s thought leadership in the technology domain * Inspire, coach and develop multidisciplinary engineering and development teams ## Qualifications * 10+ years of experience as Chief lead architect or head of an IT department in a mid-size to large business * Proven track record in shaping and delivering large-scale Engineering, Cloud, AI and Data transformation programmes end-to-end * Acts as a trusted advisor to C-level and C-1 stakeholders, bridging business strategy and technology execution * Extensive experience advising senior executives and acting as a strategic partner * Deep passion for technology, combining broad knowledge with strong depth in key domains * Able to simplify complex technical topics into clear, actionable insights * In-depth experience with modern technology stacks such as: cloud platforms: AWS, Azure, GCP; cloud-native architectures such as microservices, serverless and Kubernetes * data and AI platforms: Databricks, Snowflake, real-time data streaming and MLOps * generative AI and advanced analytics: LLMs, prompt engineering, AI orchestration and responsible AI * integration and APIs: event-driven architecture and API management * DevOps and platform engineering: CI/CD, infrastructure as a code and observability * Agentic Engineering * Strong commercial mindset, with the ability to identify opportunities, shape value propositions and build long-term client relationships * Excellent communication and leadership skills, inspiring teams and aligning diverse stakeholders * Proven ability to navigate complex stakeholder environments across business and IT * Self-starter with the ability to build a business ## Additional Information As a Director within our Engineering, AI & Data practice, you will shape our strategy, driving business development, and delivering complex transformation programmes.You own client relationships at C‑suite level, translate sector challenges into pragmatic roadmaps, and take responsibility for P&L, proposals and successful programme delivery. You build and mentor multidisciplinary teams, forge partnerships with technology and ecosystem providers, and ensure solutions meet governance, privacy and ethical standards. Externally you represent the practice through thought leadership and industry engagement, turning insight into measurable business outcomes that reshape customer experience, operations and monetisation.", "summaryDescription" : "Director Engineering, AI & Data at Deloitte. Skills: Engineering, AI, Data, Cloud, Transformation. Lead strategic and commercial growth. Build and maintain CIO relationships", "postedDate" : "2026-06-15T14:39:02.000", "createdAt" : "2026-06-16T00:04:46.141", "lastUpdated" : "2026-06-16T09:38:52.329", "ingestTimestamp" : "2026-06-16T00:04:46.141", "mongoId" : "6a306b15f292fd229cfcf414", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Data transformation", "AI transformation", "Cloud transformation", "Data platforms", "Enterprise data platforms", "Emerging technologies", "Engineering blueprints", "Roadmaps", "Project lifecycle management", "Technology domain", "Multidisciplinary teams", "Development teams", "Generative AI", "Advanced analytics", "AI orchestration", "Platform engineering", "Leadership", "Mentoring", "Engineering", "AI", "Data", "Cloud", "Transformation", "Strategic vision", "Commercial drive", "Technical architecture", "Value propositions", "Client relationships", "Business development", "Programme delivery", "P&L responsibility", "Consumer Goods", "Retail", "Travel", "Services", "Hospitality", "Cloud-native architectures", "Microservices", "Serverless", "Kubernetes", "Data and AI platforms", "Real-time data streaming", "MLOps", "Integration", "APIs", "Event-driven architecture", "API management", "DevOps", "Agentic Engineering", "Responsible AI", "Databricks", "Snowflake" ], "skillCount" : 52, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Director", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Consulting", "llmIndustryConfidence" : 0.95 }, { "id" : "6a25145a74d8ee00a00bb4fb", "title" : "Data Engineering Manager, Planning and Audience Insights", "company" : "Amazon.com Services LLC", "industry" : "Data Science, Data Engineering, entertainment", "salary" : { "min" : 170000.0, "max" : 230000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Culver City, California, USA", "locations" : [ "Culver City, California, USA" ], "timestamp" : "2026-06-15T03:17:28.355", "fingerprint" : "6aa3c856387fafb46a2f01fc537040ea31717e821969bb55d633e4a39d7571e4", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10441155/apply", "externalId" : "ca490d26-9b5c-4f9c-ac4c-e2946741f12c", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Culver City", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.0211224,-118.3964660" } ], "locationText" : "Culver City, California, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "Redshift, ETL, ELT, Data modeling, Python, Java, Scala, NodeJS, Hadoop, Hive, Spark, EMR, AWS, S3, EC2, Lambda, GenAI, ML", "professionalSkills" : [ "Data governance", "Data quality", "Data reliability", "Business intelligence", "Data architecture", "Pipeline solutions", "Audience segmentation", "Content analysis", "Experimentation automation", "Marketing optimization", "Audience strategy", "Programming decisions" ], "hardSkillsList" : [ "Data pipeline development", "Data infrastructure management", "Platform capabilities", "Performance optimization", "Cost efficiency", "Scalability management", "Monitoring implementation", "Alerting implementation", "SLA implementation", "Data quality frameworks", "Cross-functional partnership", "Roadmap reviews", "Incident response", "Continuous improvement" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Data pipeline development", "level" : "intermediate" }, { "name" : "Data infrastructure management", "level" : "intermediate" }, { "name" : "Platform capabilities", "level" : "intermediate" }, { "name" : "Performance optimization", "level" : "intermediate" }, { "name" : "Cost efficiency", "level" : "intermediate" }, { "name" : "Scalability management", "level" : "intermediate" }, { "name" : "Monitoring implementation", "level" : "intermediate" }, { "name" : "Alerting implementation", "level" : "intermediate" }, { "name" : "SLA implementation", "level" : "intermediate" }, { "name" : "Data quality frameworks", "level" : "intermediate" }, { "name" : "Cross-functional partnership", "level" : "intermediate" }, { "name" : "Roadmap reviews", "level" : "intermediate" }, { "name" : "Incident response", "level" : "intermediate" }, { "name" : "Continuous improvement", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Data Engineering, AI/ML, Data Platform, Team Leadership", "majorSkillsList" : [ "Data Engineering", "AI/ML", "Data Platform", "Team Leadership" ], "coreResponsibilities" : "Lead and develop senior data engineers, Hire senior data engineers, Mentor senior data engineers, Set technical direction, Manage performance of engineers, Manage growth opportunities for engineers, Own data platform strategy, Own data platform roadmap, Manage Redshift infrastructure, Optimize Redshift infrastructure, Ensure Redshift performance, Ensure Redshift cost efficiency, Ensure Redshift availability, Ensure Redshift scalability, Own data pipelines for AI tools, Ensure reliable data flows, Ensure high-quality data flows, Drive data engineering for applications, Establish data governance standards, Enforce data governance standards, Establish data quality standards, Enforce data quality standards, Establish data reliability standards, Enforce data reliability standards, Implement monitoring, Implement alerting, Implement SLAs, Implement data quality frameworks, Partner cross-functionally, Translate business requirements, Design scalable data architecture, Design pipeline solutions, Represent data engineering in forums, Contribute to annual planning, Contribute to QBRs, Contribute to roadmap reviews, Communicate trade-offs, Communicate capacity constraints, Communicate investment needs, Drive operational excellence, Own on-call processes, Manage incident response, Manage COE follow-ups, Improve operational posture", "teamCollaboration" : "Product managers; Data scientists; Analytics; BI engineers; Software engineers; Content programmers; Marketing strategists; Senior leadership", "projectManagementSkills" : [ "Roadmap planning", "Annual planning", "QBRs" ], "domainKnowledge" : "Prime Video; Audience Insights; Streaming services; Content programming; Marketing optimization; Audience growth; AI Tooling; Automation; Audience Infrastructure; Customer journey; Marketplace intelligence; Competitive intelligence; Digital creative production; Ad serving; Cross-channel attribution; Media analytics", "domainList" : [ "prime-video", "audience-insights", "streaming-services", "content-programming", "marketing-optimization", "audience-growth", "ai-tooling", "automation", "audience-infrastructure", "customer-journey", "marketplace-intelligence", "competitive-intelligence", "digital-creative-production", "ad-serving", "cross-channel-attribution", "media-analytics" ], "domainSpecificKnowledge" : [ "Prime Video", "Audience Insights", "Streaming services", "Content programming", "Marketing optimization", "Audience growth", "AI Tooling", "Automation", "Audience Infrastructure", "Customer journey", "Marketplace intelligence", "Competitive intelligence", "Digital creative production", "Ad serving", "Cross-channel attribution", "Media analytics" ], "toolProficiency" : [ "Redshift clusters", "Jenkins", "Bamboo", "TeamCity", "Code Deploy", "GitLab" ], "communicationSkills" : "Verbal communication; Written communication", "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "specialRequirements" : "On-call processes", "qualificationsBasic" : "7+ years data engineering experience, Experience managing data/BI team, 5+ years processing data with massively parallel technology, 3+ years developing/operating large-scale data structures for BI analytics, Experience leading/influencing data/BI strategy, Experience communicating to senior management, Experience communicating to customers, Experience in scripting or programming language", "qualificationsPreferred" : "Experience with big data technologies, Experience with AWS Tools, Experience working with Data & AI technologies, Knowledge of digital creative production, Knowledge of ad serving, Knowledge of cross-channel attribution, Knowledge of media analytics, Experience developing cloud native CI/CD workflows", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming across thousands of devices, from award-winning Amazon MGM Studios originals to live sports, channels, and TVOD. Behind the content our customers love is a team shaping what gets released, when, and for whom. The US Planning & Audience Insights team is where strategy meets data meets AI: we build the tools and intelligence that power programming decisions, audience growth, and marketing optimizations. We’re looking for a Data Engineering Manager to lead the Data Engineering function within Prime Video’s US Planning & Audience Insights team. This team defines Prime Video’s north star (long-term strategy, priority audiences, and growth objectives) and delivers the customer intelligence, analytics, and AI-powered solutions that enable the organization to achieve them. You’ll lead a team of senior data engineers and own the data infrastructure, pipelines, and platform capabilities that power our analytics, AI tools, and business-critical applications. Your team’s work directly enables content programming, marketing optimization, and audience strategy for one of the world’s largest streaming services. This requires you to balance competing priorities, manage complex stakeholder relationships, and work shoulder-to-shoulder with product managers, data scientists, and analytics to deliver scalable data solutions at pace. Key job responsibilities • Lead and develop a team of senior data engineers, hiring, mentoring, setting technical direction, managing performance and growth opportunities. • Own the data platform strategy and roadmap for the team’s portfolio, including multiple Redshift clusters, ETL/ELT pipelines, and data models that serve analytics, data science, and business stakeholders. • Manage and optimize Redshift infrastructure, ensuring performance, cost efficiency, availability, and scalability across multiple clusters serving diverse business lines. • Own data pipelines for AI-powered tools, ensuring reliable, high-quality data flows that power the team’s GenAI and ML applications including content analysis, audience segmentation, and experimentation automation. • Drive data engineering for business-critical applications, including dashboards and other internal self developed software products. • Establish and enforce data governance, quality, and reliability standards, implementing monitoring, alerting, SLAs, and data quality frameworks across the team’s data assets. • Partner cross-functionally with product managers, data scientists, BI engineers, and software engineers to translate business requirements into scalable data architecture and pipeline solutions. • Represent data engineering in planning and leadership forums, contributing to annual planning, QBRs, and roadmap reviews. Communicate trade-offs, capacity constraints, and investment needs clearly to senior leadership. • Drive operational excellence, owning on-call processes, incident response, COE follow-ups, and continuous improvement of the team’s operational posture. About the team The US Planning & Audience Insights team sits within US Prime Video. We operate across six functions: Business Planning, Product-Tech, Analytics, Data Science, Data Engineering, and Research. Our stakeholders span content programming, content acquisition, marketing, and PV senior leadership. Our 2026 roadmap is anchored in two investment themes (AI Tooling & Automation and Audience Infrastructure & Insights) spanning content optimization, experimentation, marketing, customer journey, marketplace, and competitive intelligence. Our products serve content programmers, marketing strategists, and senior leadership. We build tools that help PV decide what to release, when to release it, who to target, and how to measure success at scale. Basic Qualifications: - 7+ years of data engineering experience - Experience managing a data or BI team - 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience - 3+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience - Experience leading and influencing the data or BI strategy of your team or organization - Experience communicating to senior management and customers verbally and in writing - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS Preferred Qualifications: - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with AWS Tools and Technologies (Redshift, S3, EC2) - Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage - Knowledge of digital creative production, ad serving, cross-channel attribution, and media analytics - Experience developing cloud native CI/CD workflows and tools, such as Jenkins, Bamboo, TeamCity, Code Deploy (AWS) or GitLab Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Culver City - 170,000.00 - 230,000.00 USD annually USA, WA, SEATTLE - 170,000.00 - 230,000.00 USD annually", "summaryDescription" : "Data Engineering Manager, Planning and Audience Insights at Amazon.com Services LLC. Skills: Data Engineering, AI/ML, Data Platform, Team Leadership. Lead and develop senior data engineers. Hire senior data engineers", "postedDate" : "2026-06-13T10:46:12.112", "createdAt" : "2026-06-13T10:46:12.112", "lastUpdated" : "2026-06-15T03:17:28.355", "ingestTimestamp" : "2026-06-13T10:46:12.112", "mongoId" : "6a25145a74d8ee00a00bb4fb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10441155/apply", "salaryAnnualMin" : 170000, "salaryAnnualMax" : 230000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipeline development", "Data infrastructure management", "Platform capabilities", "Performance optimization", "Cost efficiency", "Scalability management", "Monitoring implementation", "Alerting implementation", "SLA implementation", "Data quality frameworks", "Cross-functional partnership", "Roadmap reviews", "Incident response", "Continuous improvement", "Leadership", "Mentoring", "Data Engineering", "AI/ML", "Data Platform", "Team Leadership", "Data governance", "Data quality", "Data reliability", "Business intelligence", "Data architecture", "Pipeline solutions", "Audience segmentation", "Content analysis", "Experimentation automation", "Marketing optimization", "Audience strategy", "Programming decisions", "Roadmap planning", "Annual planning", "QBRs", "Prime Video", "Audience Insights", "Streaming services", "Content programming", "Audience growth", "AI Tooling", "Automation", "Audience Infrastructure", "Customer journey", "Marketplace intelligence", "Competitive intelligence", "Digital creative production", "Ad serving", "Cross-channel attribution", "Media analytics", "Redshift clusters", "Jenkins", "Bamboo", "TeamCity", "Code Deploy", "GitLab" ], "skillCount" : 56, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2176c774d8ee00a0c1adbc", "title" : "Data Engineer, WW Promotions Data and Insights", "company" : "Amazon Development Centre Canada ULC", "industry" : "Data Science, Data Engineering, north america stores", "salary" : { "min" : 103300.0, "max" : 172600.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, CAN", "locations" : [ "Vancouver, British Columbia, CAN" ], "timestamp" : "2026-06-15T03:12:51.771", "fingerprint" : "be379a15adb0d165f4e7fbac44c1dc26058391c402487f29249070d19d908bff", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10438823/apply", "externalId" : "88a730ec-f4bb-4fe3-bfe8-4633080161a6", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "AWS, Redshift, S3, Glue, EMR, Kinesis, Lambda, Python, Scala, Airflow", "professionalSkills" : [ "Data modeling", "Data warehousing", "ETL pipelines", "Infrastructure-as-code", "CI/CD" ], "hardSkillsList" : [ "Data processing systems", "Data pipeline performance", "Data reliability", "Cost-efficiency" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "Data processing systems", "level" : "intermediate" }, { "name" : "Data pipeline performance", "level" : "intermediate" }, { "name" : "Data reliability", "level" : "intermediate" }, { "name" : "Cost-efficiency", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Data engineering, AWS services, Data pipelines", "majorSkillsList" : [ "Data engineering", "AWS services", "Data pipelines" ], "coreResponsibilities" : "Design data processing systems, Build data processing systems, Operate data processing systems, Leverage expertise in Python, Develop custom data processing frameworks, Develop automation tools, Collaborate with data scientists, Collaborate with analysts, Collaborate with product managers, Optimize data pipeline performance, Optimize data pipeline reliability, Optimize data pipeline cost-efficiency, Mentor junior engineers, Share knowledge of data engineering, Stay up-to-date with big data technologies, Stay up-to-date with architectural patterns, Drive adoption of innovative solutions", "teamCollaboration" : "With data scientists; With analysts; With product managers", "domainKnowledge" : "Promotions data; Promotional strategies; Selling Partners; Big data technologies; Architectural patterns", "domainList" : [ "promotions-data", "promotional-strategies", "selling-partners", "big-data-technologies", "architectural-patterns" ], "domainSpecificKnowledge" : [ "Promotions data", "Promotional strategies", "Selling Partners", "Big data technologies", "Architectural patterns" ], "toolProficiency" : [ "Airflow", "Redshift", "S3", "Glue", "EMR", "Kinesis", "Lambda" ], "continuousLearning" : "Stay up-to-date with technologies; Drive adoption of solutions", "innovationCreativity" : "Drive adoption of innovative solutions", "problemSolvingSkills" : "Translate business requirements", "qualificationsBasic" : "3+ years of data engineering experience, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines", "qualificationsPreferred" : "Experience with AWS technologies, Experience with non-relational databases, Usage of generative AI tools, Willingness to learn AI prompting, Ability to recognize AI opportunities", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you passionate about developing the next generation of data infrastructure capable of handling complex, mission-critical data pipelines and analytics workloads? Do you want to build next generation data engineering solutions that leverage the latest AWS technologies to process a broad range of business and customer data? Join our WW Promotions Data and Insights team, where you'll have the opportunity to continuously improve the systems that enable Amazon's promotional strategies across every major shopping event worldwide. Key job responsibilities 1. Design, build, and operate highly scalable, fault-tolerant data processing systems using modern AWS services like Redshift, S3, Glue, EMR, Kinesis, and Lambda, and orchestration systems using Airflow 2. Leverage your expertise in Python, Scala, or other modern programming languages to develop custom data processing frameworks and automation tools 3. Collaborate closely with data scientists, analysts, and product managers to understand business requirements and translate them into technical solutions 4. Continuously optimize data pipeline performance, reliability, and cost-efficiency using best practices in CI/CD and infrastructure-as-code 5. Mentor junior engineers and share your knowledge of data engineering best practices 6. Stay up-to-date with the latest big data technologies and architectural patterns, and drive the adoption of innovative solutions About the team Promotions reinforce a positive perception of Amazon’s price leadership with shoppers by complementing our everyday great prices with time-bound discounts on a broad selection of high-quality products. For Selling Partners (SPs), promotions create incremental demand for their products and increase their share of voice, clear inventory, and drive traffic to new selection. WW Promotions owns the sourcing and execution of promotions at Amazon and we are their data & analytics team. We serve as the central stewards of promotions data, delivering trusted and governed datasets that power product development, machine learning models, and business analytics across the organization. Basic Qualifications: - 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines Preferred Qualifications: - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) - Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices. - Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status. CAN, BC, Vancouver - 103,300.00 - 172,600.00 CAD annually", "summaryDescription" : "Data Engineer, WW Promotions Data and Insights at Amazon Development Centre Canada ULC. Skills: Data engineering, AWS services, Data pipelines. Design data processing systems. Build data processing systems", "postedDate" : "2026-06-13T09:12:42.868", "createdAt" : "2026-06-13T09:12:42.868", "lastUpdated" : "2026-06-15T03:12:51.771", "ingestTimestamp" : "2026-06-13T09:12:42.868", "mongoId" : "6a2176c774d8ee00a0c1adbc", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10438823/apply", "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data processing systems", "Data pipeline performance", "Data reliability", "Cost-efficiency", "Mentoring", "Data engineering", "AWS services", "Data pipelines", "Data modeling", "Data warehousing", "ETL pipelines", "Infrastructure-as-code", "CI/CD", "Promotions data", "Promotional strategies", "Selling Partners", "Big data technologies", "Architectural patterns", "Airflow", "Redshift", "S3", "Glue", "EMR", "Kinesis", "Lambda" ], "skillCount" : 25, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2176b974d8ee00a0c1aae8", "title" : "Data Engineer, Sales Insights, Analytics, Data Engineering and Science (SIADS)", "company" : "Amazon Web Services Singapore Private Limited", "industry" : "Corporate Operations, Sales Operations Job Family, Cloud Computing", "salary" : { "min" : 145000.0, "max" : 220000.0, "currency" : "SGD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Data Engineers in Singapore, adjusted for a large technology company in the tech industry." }, "location" : "SGP", "locations" : [ "SGP" ], "timestamp" : "2026-06-15T03:12:27.872", "fingerprint" : "e743dd4970a06dddb44853c58cb6544861b6823695ae01c55858ea95f7178c57", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10439385/apply", "externalId" : "0f14592e-9a1e-48c1-83bd-1045ad55e48a", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Singapore", "country" : "Singapore", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "1.2899175,103.8519072" } ], "locationText" : "Singapore, Singapore", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, AWS, Spark, AWS Glue", "professionalSkills" : [ "Data engineering", "Business intelligence", "Regional strategy", "Data models", "Analytical platforms", "Data quality", "Data governance" ], "hardSkillsList" : [ "Data transformation", "Data pipelines", "Cloud computing", "ETL processes", "Data ingestion", "Data quality validation" ], "hardSkills" : [ { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Cloud computing", "level" : "intermediate" }, { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "Data quality validation", "level" : "intermediate" } ], "majorSkills" : "Data engineering, Data analytics, Data infrastructure", "majorSkillsList" : [ "Data engineering", "Data analytics", "Data infrastructure" ], "coreResponsibilities" : "Own design, development, and maintenance of data analytics, Build and maintain APJ-specific data models and pipelines, Validate data quality against WW business standards, Design and maintain backend data infrastructure for analytics, Implement ETL processes, Develop monitoring capabilities for data quality and query, Collaborate on design and delivery of metrics, reports,, Ensure pipelines and data products meet requirements, Maintain compliance with information security policies, Maintain compliance with data governance standards", "teamCollaboration" : "Partnering with key stakeholders; Cross-functional agile teams; Regional leadership", "domainKnowledge" : "Sales operations; Finance; Business logic; Analytical requirements; Information security; Data governance", "domainList" : [ "sales-operations", "finance", "business-logic", "analytical-requirements", "information-security", "data-governance" ], "domainSpecificKnowledge" : [ "Sales operations", "Finance", "Business logic", "Analytical requirements", "Information security", "Data governance" ], "toolProficiency" : [ "SQL", "AWS", "Terraform", "CloudFormation", "CDK", "Apache Spark", "AWS Glue" ], "communicationSkills" : "Written communication; Verbal communication", "problemSolvingSkills" : "Data-driven decision making", "outcomesObjectives" : "Deliver data products that matter; Power SMGS business insights; Keep platforms reliable and responsive; Drive key business decisions", "qualificationsBasic" : "Written and verbal communication skills, Competent in performing data transformation using SQL, Experienced in managing and maintaining data pipelines, Proficient in cloud computing platforms (e.g., AWS)", "qualificationsPreferred" : "Experienced in Infrastructure-as-Code, Skilled in designing system solutions at scale, Knowledgeable in Apache Spark, Proficient in serverless ETL using AWS Glue, Skilled in automating data quality validation", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Join the cloud platform trusted by millions worldwide and own the data infrastructure that powers strategic business decisions across Asia Pacific and Japan (APJ). This is a hands-on, technically demanding role for an experienced data engineer who is passionate about building robust data products that enable teams to measure and grow the business. You will be part of a team that operates at the intersection of data engineering, business intelligence, and regional strategy, partnering with key stakeholders (e.g. Sales, Sales Operations, Finance, etc.), and regional leadership to deliver data products that matter. If you thrive in a fast-paced, high-growth environment where ownership, technical depth, and business judgement are equally valued — and where your pipelines, data models, and analytics platforms will serve field teams across key verticals and business units across APJ — this role is for you. Key job responsibilities - Own the design, development, and maintenance of the APJ SIADS' data analytics platform, including data pipelines, data lakes, and analytical and visualisation platforms that power SMGS business insights - Build and maintain APJ-specific data models and pipelines, ensuring alignment between worldwide definitions and APJ business logic, and validating data quality against WW business standards - Design and maintain the backend data infrastructure for end-user last-mile analytics tools, implementing ETL processes that ensure data is clean, fresh, and optimised for APJ analytical requirements - Develop monitoring capabilities for data quality and query performance to keep platforms reliable and responsive - Collaborate on the design and delivery of metrics, reports, analyses, and dashboards that drive key business decisions across APJ, in partnership with key stakeholders e.g., Sales, Sales Operations, Finance, etc. - Ensure pipelines and data products meet the requirements of field teams across key verticals and business units - Maintain compliance with information security policies and data governance standards for all infrastructure and software used by the team About the team The Sales Insights, Analytics, Data Engineering & Science (SIADS) organisation builds the data infrastructure and analytics products that power business decisions across AWS' Sales, Marketing, and Global Services (SMGS) organisation. We sit at the intersection of engineering and business strategy, partnering with key stakeholders (e.g., Sales, Sales Operations, Finance, etc.) to ensure the right data reaches the right people at the right time. Operating across time zones with both global and regional depth, we value technical excellence, sound business judgement, and clear communication. Amazon's data-driven culture starts here — and your work will be central to it. Basic Qualifications: - Strong written and verbal communication skills - Competent in performing data transformation using SQL - Experienced in managing and maintaining data pipelines - Proficient in cloud computing platforms (e.g., AWS) Preferred Qualifications: - Experienced in Infrastructure-as-Code (e.g., Terraform, CloudFormation, CDK) - Skilled in designing system solutions at scale - Knowledgeable in Apache Spark for large-scale data workloads - Proficient in serverless ETL using AWS Glue for data ingestion, transformation, and cataloguing - Skilled in automating data quality validation to detect anomalies and enforce data integrity Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Data Engineer, Sales Insights, Analytics, Data Engineering and Science (SIADS) at Amazon Web Services Singapore Private Limited. Skills: Data engineering, Data analytics, Data infrastructure. Own design, development, and maintenance of data analytics. Build and maintain APJ-specific data models and pipelines", "postedDate" : "2026-06-13T09:12:16.971", "createdAt" : "2026-06-13T09:12:16.971", "lastUpdated" : "2026-06-15T03:12:27.872", "ingestTimestamp" : "2026-06-13T09:12:16.971", "mongoId" : "6a2176b974d8ee00a0c1aae8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10439385/apply", "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data transformation", "Data pipelines", "Cloud computing", "ETL processes", "Data ingestion", "Data quality validation", "Data engineering", "Data analytics", "Data infrastructure", "Business intelligence", "Regional strategy", "Data models", "Analytical platforms", "Data quality", "Data governance", "Sales operations", "Finance", "Business logic", "Analytical requirements", "Information security", "SQL", "AWS", "Terraform", "CloudFormation", "CDK", "Apache Spark", "AWS Glue" ], "skillCount" : 27, "jobCategory" : "operations", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a210e4274d8ee00a0af6952", "title" : "AI and Data Engineer, Google Cloud", "company" : "Google", "industry" : "Technology", "salary" : { "min" : 3500000.0, "max" : 5500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for AI and Data Engineer roles in Bengaluru, India, adjusted for mid-seniority at a large technology company." }, "location" : "[Bengaluru, Karnataka, India, [3, Old Madras Rd, Sadanandanagar, Bennigana Halli, Bengaluru, Karnataka 560038, India], Bengaluru, 560038, KA, IN]", "locations" : [ "[Bengaluru, Karnataka, India, [3, Old Madras Rd, Sadanandanagar, Bennigana Halli, Bengaluru, Karnataka 560038, India], Bengaluru, 560038, KA, IN]" ], "timestamp" : "2026-06-16T13:35:46.278", "fingerprint" : "54c8f088fb0672edc0ea6a7f5bbfd01198b4f714dbf06ba36b9acd3dc018273a", "source" : "google", "language" : "en", "externalId" : "86594383251415750", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "remoteFriendly" : false, "summaryDescription" : "AI and Data Engineer, Google Cloud at Google", "postedDate" : "2026-06-16T01:48:26.891", "createdAt" : "2026-06-16T01:48:26.891", "lastUpdated" : "2026-06-16T13:35:46.278", "ingestTimestamp" : "2026-06-16T01:48:26.891", "mongoId" : "6a210e4274d8ee00a0af6952", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.5555556, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306768f292fd229cfbca30", "title" : "Director, Customer Success Data Engineering", "company" : "Toast", "industry" : "Hospitality", "salary" : { "min" : 215000.0, "max" : 315000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data for Director, Customer Success Data Engineering in Boston, MA, adjusted for SaaS industry and company size." }, "location" : "Boston, MA, United States", "locations" : [ "Boston", "MA", "United States" ], "timestamp" : "2026-06-16T08:48:07.601", "fingerprint" : "4bc71b5b4b23b4cb5ae7edae2bd63402c6637390ab8750f65e7e773bf34672c5", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://careers.toasttab.com/jobs?gh_jid=8008019", "externalId" : "8008019", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Data modeling", "Analytics engineering", "AI data strategy", "Data architecture", "Pipeline development", "System design" ], "hardSkillsList" : [ "Data integration", "Data modeling", "Pipeline optimization", "Data quality monitoring", "KPI definition", "Data lineage", "Governance standards" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Data integration", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Pipeline optimization", "level" : "intermediate" }, { "name" : "Data quality monitoring", "level" : "intermediate" }, { "name" : "KPI definition", "level" : "intermediate" }, { "name" : "Data lineage", "level" : "intermediate" }, { "name" : "Governance standards", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Data architecture, AI data strategy, Data modeling, Leadership", "majorSkillsList" : [ "Data architecture", "AI data strategy", "Data modeling", "Leadership" ], "coreResponsibilities" : "Own the redesign of the unified CS data, Connect data across Care, CX, Enablement, and CSS, Define and execute the AI data strategy for, Make active architectural decisions for AI data retrieval, Build and maintain a documentation layer, Develop and apply a clear framework for AI, Lead the data integration for the contact center, Design and optimize pipelines for analytics, reporting, and, Establish testing, monitoring, and alerting as standard practice, Manage and mentor two senior data and analytics, Serve as the primary data architecture partner for, Collaborate closely with cross-functional peers, Represent CS data interests in enterprise governance forums, Ensure CS data is accurate, accessible, and trusted, Maintain a shared KPI dictionary, Maintain a data lineage map, Maintain a self-service analytics framework, Establish clear SLAs for data delivery, Establish processes for ongoing data quality monitoring", "teamCollaboration" : "Cross-functional peers; CS analytics and operations leaders; Enterprise data infrastructure; Finance; Business technology; Centralized data teams; Enterprise governance forums", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Customer Success data; Contact center platform; AI consumption; Semantic layer; Data quality; Data governance", "domainList" : [ "customer-success-data", "contact-center-platform", "ai-consumption", "semantic-layer", "data-quality", "data-governance" ], "domainSpecificKnowledge" : [ "Customer Success data", "Contact center platform", "AI consumption", "Semantic layer", "Data quality", "Data governance" ], "toolProficiency" : [ "Snowflake", "Dbt", "Contact center platform" ], "communicationSkills" : "Cross-functional communication", "documentationSkills" : "Documentation layer; Data documentation", "problemSolvingSkills" : "Diagnose systemic data quality and architecture problems; Redesign from the ground up", "outcomesObjectives" : "Ensure predictability and consistency of AI outputs; Ensure clean, well-modeled contact data flows; Ensure stakeholders are not the first to know something is broken; Build a high-performance team; Ensure security, compliance, and architecture standards are met; Ensure CS data is accurate, accessible, and trusted", "qualificationsBasic" : "10+ years of experience in data platform, data modeling, or analytics engineering, 3 years in a leadership capacity, Experience designing data models with AI consumption in mind, Hands-on experience with modern data stack tools, Building or maintaining a semantic layer, Track record of treating pipelines like software, Proven ability to diagnose systemic data quality and architecture problems, Cross-functional communication skill", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Role Overview This role serves as the data leader and technical authority for Customer Success data at Toast. You will own the strategy and execution of CS data modeling initiatives -- redesigning the CS data model from the ground up and defining how data is accessed, queried, and served across the organization. The CS data model needs to work reliably in two modes: as a structured foundation for dashboards, reporting, and operational metrics, and as a well-documented, trustworthy layer that AI systems can query consistently. Building for both -- and making deliberate architectural decisions about when each approach is appropriate -- is central to this role. This is an embedded role, sitting inside the CS organization. CS data problems are business problems first -- understanding how customers are being supported, where friction exists, and what patterns predict risk or opportunity requires close proximity to the teams asking those questions. This role is positioned to build that context directly and translate it into data architecture decisions. You will lead a small team of two senior data and analytics engineers to start, with room to grow as the function matures. What You'll Do Data Architecture & AI Data Strategy Own the redesign of the unified CS data model, connecting data across Care, CX, Enablement, and CSS teams and source systems including our new contact center platform. Define and execute the AI data strategy for CS -- specifically, how AI accesses, queries, and interacts with the data model. This means making active architectural decisions about when to pre-calculate and structure data versus when to allow dynamic AI retrieval, with predictability and consistency of outputs as the governing constraint. Build and maintain a documentation layer that functions as a first-class artifact -- not an afterthought. Reliable AI data access depends on well-structured, accurate documentation, and this person will treat it that way. Develop and apply a clear framework for when AI is the right tool versus traditional data approaches. Part of the job is pushing back when AI is unnecessary or introduces reliability risk. Platform & Pipeline Development Lead the data integration for the contact center platform migration, ensuring clean, well-modeled contact data flows into the CS data layer from day one. Design and optimize pipelines for analytics, reporting, and AI/ML-driven use cases. Establish testing, monitoring, and alerting as standard practice across CS pipelines -- freshness checks, completeness validation, anomaly detection. Stakeholders should never be the first to know something is broken. Leadership & Cross-functional Partnership Manage and mentor two senior data and analytics engineers, providing clear direction and building a high-performance team from the ground up. Serve as the primary data architecture partner for CS analytics and operations leaders, translating business problems into data model and tooling decisions. Collaborate closely with cross-functional peers in CS analytics, enterprise data infrastructure, finance, and business technology to align on KPI definitions, data lineage, and governance standards. Represent CS data interests in enterprise governance forums, ensuring security, compliance, and architecture standards are met. Enablement & Governance Ensure CS data is accurate, accessible, and trusted by the teams who depend on it -- from strategic OKRs down to operational dashboards. Maintain a shared KPI dictionary, data lineage map, and self-service analytics framework in partnership with centralized data teams. Establish clear SLAs for data delivery and processes for ongoing data quality monitoring. What We're Looking For Required Qualifications 10+ years of experience in data platform, data modeling, or analytics engineering roles, with at least 3 years in a leadership capacity. Experience designing data models with AI consumption in mind -- structuring for retrieval versus pre-calculation tradeoffs, ensuring predictability of outputs, and understanding that documentation is infrastructure, not overhead. Hands-on experience with modern data stack tools -- Snowflake, dbt, or equivalent -- including building or maintaining a semantic layer that ensures consistent metric definitions across BI tools, notebooks, and AI agents. A track record of treating pipelines like software: automated tests, schema validation, freshness and completeness monitoring, and changes that go through review before they reach production. You have been burned by silent data failures and build accordingly. Proven ability to diagnose systemic data quality and architecture problems and redesign from the ground up -- not just patch on top of what exists. Strong cross-functional communication skills -- you can translate complex data architecture decisions for non-technical business stakeholders. Preferred Qualifications Experience working in Customer Success, SaaS, or customer-facing operational analytics environments. Familiarity with Snowflake and modern orchestration frameworks (dbt, Airflow, or equivalent). Background that skews toward data modeling and transformation work -- you think in terms of data models, schemas, and semantic layers rather than services and application infrastructure. Experience with BI tools and dashboarding. Familiarity with real-time data streaming technologies (Kafka, Kinesis, or equivalent). Who Will Thrive Here You are energized by greenfield work. This role is building something new, and the fingerprints you leave on the data model and AI strategy will be visible and lasting. You are comfortable with a lean team today. Two direct reports to start, with room to grow -- this is not a role for someone who needs org size to feel impactful. You have the judgment to advocate for the right use of AI, including knowing when not to use it. The goal is a trustworthy, reliable data layer -- not AI for its own sake. You are a builder first. Strategy matters, but so does the ability to roll up your sleeves and make decisions at the implementation level. The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy. Zone A $217,000—$347,000 USD Zone B $188,000—$301,000 USD Zone C $170,000—$272,000 USD How Toast Uses AI in its Hiring Process Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: https://careers.toasttab.com/ai-in-hiring Our Approach to Hybrid Working We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: https://careers.toasttab.com/locations-toast Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences. We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast. Apply today! Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com. ------ For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.", "summaryDescription" : "Director, Customer Success Data Engineering at Toast. Skills: Data architecture, AI data strategy, Data modeling, Leadership. Own the redesign of the unified CS data. Connect data across Care, CX, Enablement, and CSS", "postedDate" : "2026-06-15T23:29:38.401", "createdAt" : "2026-06-15T23:29:38.401", "lastUpdated" : "2026-06-16T08:48:07.601", "ingestTimestamp" : "2026-06-15T23:29:38.401", "mongoId" : "6a306768f292fd229cfbca30", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 215000, "salaryAnnualMax" : 315000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Data integration", "Data modeling", "Pipeline optimization", "Data quality monitoring", "KPI definition", "Data lineage", "Governance standards", "Leadership", "Mentoring", "Data architecture", "AI data strategy", "Analytics engineering", "Pipeline development", "System design", "Roadmap planning", "Customer Success data", "Contact center platform", "AI consumption", "Semantic layer", "Data quality", "Data governance", "Snowflake", "Dbt" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a306768f292fd229cfbca2f", "title" : "Director, Customer Success Data Engineering", "company" : "Toast", "industry" : "Hospitality", "salary" : { "min" : 225000.0, "max" : 325000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data for Director, Customer Success Data Engineering in Boston, MA, adjusted for industry and company size." }, "location" : "Boston, MA, United States", "locations" : [ "Boston", "MA", "United States" ], "timestamp" : "2026-06-16T08:07:05.763", "fingerprint" : "2be800f3b4781e8517e37946b154448302fc38ae75cd01902e2c759340d450b7", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://careers.toasttab.com/jobs?gh_jid=7951246", "externalId" : "7951246", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "SQL, Python, Snowflake, Dbt, AI", "professionalSkills" : [ "Data modeling", "Data architecture", "System design" ], "hardSkillsList" : [ "Data engineering", "Analytics engineering", "AI data strategy", "Data integration", "Pipeline development", "Data quality monitoring", "Data governance" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "Analytics engineering", "level" : "intermediate" }, { "name" : "AI data strategy", "level" : "intermediate" }, { "name" : "Data integration", "level" : "intermediate" }, { "name" : "Pipeline development", "level" : "intermediate" }, { "name" : "Data quality monitoring", "level" : "intermediate" }, { "name" : "Data governance", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Data architecture, AI data strategy, Data modeling", "majorSkillsList" : [ "Data architecture", "AI data strategy", "Data modeling" ], "coreResponsibilities" : "Own the redesign of the unified CS data, Connect data across Care, CX, Enablement, and CSS, Define and execute the AI data strategy for, Make active architectural decisions about data calculation versus, Build and maintain a documentation layer, Develop and apply a clear framework for AI, Lead the data integration for the contact center, Design and optimize pipelines for analytics, reporting, and, Establish testing, monitoring, and alerting as standard practice, Manage and mentor two senior data and analytics, Serve as the primary data architecture partner for, Collaborate closely with cross-functional peers, Represent CS data interests in enterprise governance forums, Ensure CS data is accurate, accessible, and trusted, Maintain a shared KPI dictionary, Maintain a data lineage map, Maintain a self-service analytics framework, Establish clear SLAs for data delivery, Establish processes for ongoing data quality monitoring", "teamCollaboration" : "CS analytics and operations leaders; Cross-functional peers; Centralized data teams; Enterprise governance forums", "domainKnowledge" : "Customer Success; Contact center platform; AI systems", "domainList" : [ "customer-success", "contact-center-platform", "ai-systems" ], "domainSpecificKnowledge" : [ "Customer Success", "Contact center platform", "AI systems" ], "toolProficiency" : [ "Snowflake", "Dbt" ], "communicationSkills" : "Cross-functional communication", "documentationSkills" : "Documentation layer", "problemSolvingSkills" : "Diagnose systemic data quality and architecture problems", "qualificationsBasic" : "10+ years of experience in data platform, data modeling, or analytics engineering, 3+ years in a leadership capacity, Experience designing data models with AI consumption in mind, Hands-on experience with modern data stack tools, Building or maintaining a semantic layer, Track record of treating pipelines like software, Proven ability to diagnose systemic data quality and architecture problems, Cross-functional communication skill", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Role Overview This role serves as the data leader and technical authority for Customer Success data at Toast. You will own the strategy and execution of CS data modeling initiatives -- redesigning the CS data model from the ground up and defining how data is accessed, queried, and served across the organization. The CS data model needs to work reliably in two modes: as a structured foundation for dashboards, reporting, and operational metrics, and as a well-documented, trustworthy layer that AI systems can query consistently. Building for both -- and making deliberate architectural decisions about when each approach is appropriate -- is central to this role. This is an embedded role, sitting inside the CS organization. CS data problems are business problems first -- understanding how customers are being supported, where friction exists, and what patterns predict risk or opportunity requires close proximity to the teams asking those questions. This role is positioned to build that context directly and translate it into data architecture decisions. You will lead a small team of two senior data and analytics engineers to start, with room to grow as the function matures. What You'll Do Data Architecture & AI Data Strategy Own the redesign of the unified CS data model, connecting data across Care, CX, Enablement, and CSS teams and source systems including our new contact center platform. Define and execute the AI data strategy for CS -- specifically, how AI accesses, queries, and interacts with the data model. This means making active architectural decisions about when to pre-calculate and structure data versus when to allow dynamic AI retrieval, with predictability and consistency of outputs as the governing constraint. Build and maintain a documentation layer that functions as a first-class artifact -- not an afterthought. Reliable AI data access depends on well-structured, accurate documentation, and this person will treat it that way. Develop and apply a clear framework for when AI is the right tool versus traditional data approaches. Part of the job is pushing back when AI is unnecessary or introduces reliability risk. Platform & Pipeline Development Lead the data integration for the contact center platform migration, ensuring clean, well-modeled contact data flows into the CS data layer from day one. Design and optimize pipelines for analytics, reporting, and AI/ML-driven use cases. Establish testing, monitoring, and alerting as standard practice across CS pipelines -- freshness checks, completeness validation, anomaly detection. Stakeholders should never be the first to know something is broken. Leadership & Cross-functional Partnership Manage and mentor two senior data and analytics engineers, providing clear direction and building a high-performance team from the ground up. Serve as the primary data architecture partner for CS analytics and operations leaders, translating business problems into data model and tooling decisions. Collaborate closely with cross-functional peers in CS analytics, enterprise data infrastructure, finance, and business technology to align on KPI definitions, data lineage, and governance standards. Represent CS data interests in enterprise governance forums, ensuring security, compliance, and architecture standards are met. Enablement & Governance Ensure CS data is accurate, accessible, and trusted by the teams who depend on it -- from strategic OKRs down to operational dashboards. Maintain a shared KPI dictionary, data lineage map, and self-service analytics framework in partnership with centralized data teams. Establish clear SLAs for data delivery and processes for ongoing data quality monitoring. What We're Looking For Required Qualifications 10+ years of experience in data platform, data modeling, or analytics engineering roles, with at least 3 years in a leadership capacity. Experience designing data models with AI consumption in mind -- structuring for retrieval versus pre-calculation tradeoffs, ensuring predictability of outputs, and understanding that documentation is infrastructure, not overhead. Hands-on experience with modern data stack tools -- Snowflake, dbt, or equivalent -- including building or maintaining a semantic layer that ensures consistent metric definitions across BI tools, notebooks, and AI agents. A track record of treating pipelines like software: automated tests, schema validation, freshness and completeness monitoring, and changes that go through review before they reach production. You have been burned by silent data failures and build accordingly. Proven ability to diagnose systemic data quality and architecture problems and redesign from the ground up -- not just patch on top of what exists. Strong cross-functional communication skills -- you can translate complex data architecture decisions for non-technical business stakeholders. Preferred Qualifications Experience working in Customer Success, SaaS, or customer-facing operational analytics environments. Familiarity with Snowflake and modern orchestration frameworks (dbt, Airflow, or equivalent). Background that skews toward data modeling and transformation work -- you think in terms of data models, schemas, and semantic layers rather than services and application infrastructure. Experience with BI tools and dashboarding. Familiarity with real-time data streaming technologies (Kafka, Kinesis, or equivalent). Who Will Thrive Here You are energized by greenfield work. This role is building something new, and the fingerprints you leave on the data model and AI strategy will be visible and lasting. You are comfortable with a lean team today. Two direct reports to start, with room to grow -- this is not a role for someone who needs org size to feel impactful. You have the judgment to advocate for the right use of AI, including knowing when not to use it. The goal is a trustworthy, reliable data layer -- not AI for its own sake. You are a builder first. Strategy matters, but so does the ability to roll up your sleeves and make decisions at the implementation level. The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy. Zone A $217,000—$347,000 USD Zone B $188,000—$301,000 USD Zone C $170,000—$272,000 USD How Toast Uses AI in its Hiring Process Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: https://careers.toasttab.com/ai-in-hiring Our Approach to Hybrid Working We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: https://careers.toasttab.com/locations-toast Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences. We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast. Apply today! Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com. ------ For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.", "summaryDescription" : "Director, Customer Success Data Engineering at Toast. Skills: Data architecture, AI data strategy, Data modeling. Own the redesign of the unified CS data. Connect data across Care, CX, Enablement, and CSS", "postedDate" : "2026-06-15T23:29:33.956", "createdAt" : "2026-06-15T23:29:33.956", "lastUpdated" : "2026-06-16T08:07:05.763", "ingestTimestamp" : "2026-06-15T23:29:33.956", "mongoId" : "6a306768f292fd229cfbca2f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 225000, "salaryAnnualMax" : 325000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Data engineering", "Analytics engineering", "AI data strategy", "Data integration", "Pipeline development", "Data quality monitoring", "Data governance", "Leadership", "Mentoring", "Data architecture", "Data modeling", "System design", "Customer Success", "Contact center platform", "AI systems", "Snowflake", "Dbt" ], "skillCount" : 17, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a305a1cf292fd229cf4d5d3", "title" : "Data & AI Engineer", "company" : "Oxylabs", "industry" : "Oxylabs Core", "salary" : { "min" : 3400.0, "max" : 5600.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vilnius", "locations" : [ "Vilnius" ], "timestamp" : "2026-06-16T14:49:05.711", "fingerprint" : "49cbbdf7aefba67b30cbde682079478d9b825e55daafcb0fde378fb56d55b43b", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/oxylabs/f8d45b19-11ad-4d9a-9f2b-ec2c549b0fbe/apply", "externalId" : "f8d45b19-11ad-4d9a-9f2b-ec2c549b0fbe", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vilnius", "country" : "Lithuania", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "54.6870458,25.2829111" } ], "locationText" : "Vilnius, Lithuania", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, LLMs, Google Cloud Platform, AWS, Git, Terraform, Docker, SQL, Dbt, PowerBI, Superset, Airflow, Kubernetes, Argo CD, Anthropic Claude, Google Gemini, OpenAI GPT, LangChain, Claude Agent SDK, Google ADK, N8n.io, Llama, Qwen", "professionalSkills" : [ "AI coding assistants", "AI application development", "DataOps practices" ], "hardSkillsList" : [ "Prompt engineering", "Model optimization", "Benchmarking", "Monitoring systems" ], "hardSkills" : [ { "name" : "Prompt engineering", "level" : "intermediate" }, { "name" : "Model optimization", "level" : "intermediate" }, { "name" : "Benchmarking", "level" : "intermediate" }, { "name" : "Monitoring systems", "level" : "intermediate" } ], "majorSkills" : "AI Engineering, LLM Development, DataOps", "majorSkillsList" : [ "AI Engineering", "LLM Development", "DataOps" ], "coreResponsibilities" : "Build AI applications using Python, Conduct research with new LLM technologies, Share findings with team, Collaborate with cross-functional teams, Identify AI-driven opportunities, Integrate solutions into business processes, Fine-tune prompt strategies, Optimize prompt strategies, Define AI evaluation metrics, Define benchmarking frameworks, Implement monitoring systems, Track LLM performance, Track LLM costs, Promote AI adoption, Promote AI understanding", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Web data gathering; AI coding assistants; Agentic development patterns; LLM technologies", "domainList" : [ "web-data-gathering", "ai-coding-assistants", "agentic-development-patterns", "llm-technologies" ], "domainSpecificKnowledge" : [ "Web data gathering", "AI coding assistants", "Agentic development patterns", "LLM technologies" ], "toolProficiency" : [ "Git", "Terraform", "Docker", "LangChain", "Claude Agent SDK", "Google ADK", "N8n.io" ], "communicationSkills" : "Written communication; Spoken communication", "continuousLearning" : "External conferences; Mentorship; Knowledge-sharing", "innovationCreativity" : "Cutting-edge solutions; AI-powered tools", "problemSolvingSkills" : "Analytical thinking", "qualificationsBasic" : "Proficiency in at least one programming language, Hands-on experience with agentic development patterns, Experience with LLMs APIs, Knowledge of best DataOps practices, Excellent communication in Lithuanian and English", "qualificationsPreferred" : "Familiarity with agent frameworks, Proficiency in deploying open-source AI models, Background in Machine Learning beyond LLMs", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "## Description We're a team of 700+ professionals who develop cutting-edge web data gathering solutions for thousands of the world's best-known businesses, including Fortune 500 companies. The team waiting for you: As our Data & AI Engineer, you'll be diving into the technical challenges of building internal AI-powered systems to help us make better-informed business decisions at Oxylabs.io. This is an excellent opportunity for an analytical thinker who enjoys hands-on technical work, has a passion for AI technologies, is eager to learn more, and wants to make a meaningful impact. You'll be developing and deploying AI-powered tools leveraging the latest AI models (including Anthropic's Claude, Google's Gemini, OpenAI's GPT) that our internal teams will use daily. ## In this role, you’ll Build AI applications using Python, LLMs & RAG; Conduct research with new LLM technologies and frameworks (with a focus on AI coding assistants) to keep our AI capabilities at the cutting edge and share your findings with others; Collaborate with cross-functional teams to identify AI-driven opportunities and integrate various solutions into their operations; Fine-tune and optimize prompt strategies to enhance accuracy, reliability, and efficiency of LLM outputs; Define AI evaluation metrics and benchmarking frameworks and implement monitoring systems to track LLM performance and costs Promote the adoption and understanding of AI within Oxylabs. ## Your skills & experience Proficiency in at least one programming language, ideally Python; Hands-on experience with agentic development patterns and best practices (tool use, planning loops, evaluation); Experience with LLMs (e.g., Anthropic/OpenAI/Gemini APIs) and AI application development; Experience with cloud infrastructure (ideally Google Cloud or AWS); Knowledge of best DataOps practices and tools including version control systems (e.g., Git), Terraform, Docker, and CI/CD; You're excellent at communicating in both written and spoken Lithuanian and English. ## Nice to have Familiarity with agent frameworks (e.g., LangChain, Claude Agent SDK, Google ADK) or workflow automation tools (e.g., n8n.io); Proficiency in deploying and optimizing open-source AI models (e.g., Llama, Qwen); Background in Machine Learning beyond LLMs (e.g., computer vision, traditional ML). ## Tech stack Google Cloud Platform (Pub/Sub, GCS, BQ) for ingestion, storage and warehousing; dbt and SQL for data modelling; PowerBI and Superset for data visualisation. Python for automation; Airflow for orchestration; Kubernetes/Argo CD for deployment; ## Salary & Benefits Gross salary: 3400-5600 EUR/month. Keep in mind that we are open to discuss a different salary based on your skills and competencies. Growth & Learning: 40+ internal learning options, external conferences, mentorship, and year-round knowledge-sharing. Health & Well-being: Private health insurance, psychotherapy, on-site well-being consultants, 24/7 gym access, and a wellness app. Celebration & Community: Team events, an overseas workation, quarterly team-building budgets, and plenty of ways to mark milestones together. Plus bonus vacation days, paid life-moment days off, barista coffee, and all the tools you need. See the full list of benefits here: https://career.oxylabs.io/blog/our-work-benefits/. Up for the challenge? Let’s talk!", "summaryDescription" : "Data & AI Engineer at Oxylabs. Skills: AI Engineering, LLM Development, DataOps. Build AI applications using Python. Conduct research with new LLM technologies", "postedDate" : "2026-06-15T13:26:25.591", "createdAt" : "2026-06-15T13:26:25.591", "lastUpdated" : "2026-06-16T14:49:05.711", "ingestTimestamp" : "2026-06-16T03:23:13.695", "mongoId" : "6a305a1cf292fd229cf4d5d3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "<30k", "hasSalary" : false, "allSkills" : [ "Prompt engineering", "Model optimization", "Benchmarking", "Monitoring systems", "AI Engineering", "LLM Development", "DataOps", "AI coding assistants", "AI application development", "DataOps practices", "Web data gathering", "Agentic development patterns", "LLM technologies", "Git", "Terraform", "Docker", "LangChain", "Claude Agent SDK", "Google ADK", "N8n.io" ], "skillCount" : 20, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a210e2074d8ee00a0af5d5b", "title" : "Data and AI Consultant", "industry" : "Consulting", "location" : "[Johannesburg, South Africa, [222, 216 Rahima Moosa St, Johannesburg, 2001, South Africa], Johannesburg, 2001, GP, ZA]", "locations" : [ "[Johannesburg, South Africa, [222, 216 Rahima Moosa St, Johannesburg, 2001, South Africa], Johannesburg, 2001, GP, ZA]" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T11:09:43.961", "fingerprint" : "ce5f54c24f1d83855c92bcc25d7de6eb92fe29ce03d92b75ad978f7e88ee4e1a", "source" : "google", "language" : "en", "externalId" : "122332690157314758", "industryFunction" : { }, "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills" ], "hardSkillsList" : [ "Statistical analysis", "Machine learning", "Data modelling", "ETL processes", "Data warehousing", "Cloud computing", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Data modelling", "level" : "intermediate" }, { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "Cloud computing", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data Science, AI, Machine Learning, Data Engineering", "majorSkillsList" : [ "Data Science", "AI", "Machine Learning", "Data Engineering" ], "coreResponsibilities" : "Develop and implement data science solutions, Build and maintain data pipelines, Design and deploy machine learning models, Create and manage business intelligence dashboards, Analyze complex datasets, Provide insights and recommendations, Collaborate with stakeholders, Stay updated on industry trends", "teamCollaboration" : "Cross-functional teams; Client stakeholders", "domainKnowledge" : "Cloud-native architecture; Distributed systems", "domainList" : [ "cloud-native-architecture", "distributed-systems" ], "domainSpecificKnowledge" : [ "Cloud-native architecture", "Distributed systems" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Client presentations; Technical documentation", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "5+ years of experience in data science, Proficiency in SQL, Bachelor's degree in Statistics, Computer Science, Mathematics, or related field", "qualificationsPreferred" : "PhD preferred, Experience with specific ML frameworks, Cloud platform certifications", "summaryDescription" : "Data and AI Consultant. Skills: Data Science, AI, Machine Learning, Data Engineering. Develop and implement data science solutions. Build and maintain data pipelines", "postedDate" : "2026-06-16T01:48:00.642", "createdAt" : "2026-06-16T01:48:00.642", "lastUpdated" : "2026-06-16T11:09:43.961", "ingestTimestamp" : "2026-06-16T01:48:00.642", "mongoId" : "6a210e2074d8ee00a0af5d5b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "hasSalary" : false, "allSkills" : [ "Statistical analysis", "Machine learning", "Data modelling", "ETL processes", "Data warehousing", "Cloud computing", "A/B testing", "Causal inference", "Data Science", "AI", "Machine Learning", "Data Engineering", "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Cloud-native architecture", "Distributed systems", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker" ], "skillCount" : 32, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.44444445, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Consulting", "llmIndustryConfidence" : 0.0 }, { "id" : "6a307f8af292fd229c05a7f3", "title" : "Strategy and Insights Manager, Large Customer Sales", "salary" : { "min" : 120000.0, "max" : 180000.0, "currency" : "SGD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Manager in Singapore, adjusted for the Strategy and Insights Manager role in Large Customer Sales." }, "location" : "[Singapore, [Singapore], null, null, null, SG]", "locations" : [ "[Singapore, [Singapore], null, null, null, SG]", "[Jakarta, Indonesia, [Jakarta, Indonesia], Jakarta, null, Jakarta, ID]" ], "timestamp" : "2026-06-16T12:48:19.544", "fingerprint" : "fb3708c7bbeae3f28c2f462c1071d95fa82976f18f5081e0ed6c457d31ce7ae9", "source" : "google", "language" : "en", "externalId" : "121219640893285062", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Singapore", "country" : "Singapore", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "1.2899175,103.8519072" } ], "locationText" : "Singapore, Singapore", "experienceLevel" : "Manager", "remoteFriendly" : false, "summaryDescription" : "Strategy and Insights Manager, Large Customer Sales", "postedDate" : "2026-06-16T01:49:20.394", "createdAt" : "2026-06-16T01:49:20.394", "lastUpdated" : "2026-06-16T12:48:19.544", "ingestTimestamp" : "2026-06-16T01:49:20.394", "mongoId" : "6a307f8af292fd229c05a7f3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "sales", "jobSubcategory" : "revenue", "seniorityLevel" : "Manager", "dataQualityScore" : 0.5555556, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustryConfidence" : 0.9 }, { "id" : "6a306724f292fd229cfb9ac9", "title" : "Evidence and Insights Manager", "company" : "Girl Effect", "industry" : "Media", "salary" : { "min" : 3800000.0, "max" : 6500000.0, "currency" : "KES", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Evidence and Insights Manager in Kenya, adjusted for the non-profit industry and contract employment type." }, "location" : "Kenya", "locations" : [ "Kenya" ], "timestamp" : "2026-06-16T06:58:42.744", "fingerprint" : "fe282112e60fdd0b35eb9991d7b1a64b9dc9a306eafa3ea496f05e08adbd32f2", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/girleffect/jobs/8591795002", "externalId" : "8591795002", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Kenya", "continent" : "af", "workMode" : "onsite" } ], "locationText" : "Kenya", "employmentType" : "CONTRACT", "experienceMinYears" : 4, "experienceLevel" : "Manager", "professionalSkills" : [ "Applied research", "Monitoring and evaluation", "Research design", "Fieldwork", "Data analysis", "Reporting", "Commissioning research", "Managing research", "Strategic planning", "Knowledge management", "Project management" ], "hardSkillsList" : [ "Qualitative analysis", "Quantitative analysis", "Digital data analysis", "Research methods", "Data analysis", "Reporting" ], "softSkillsList" : [ "Leadership", "Negotiation", "Conflict resolution", "Public speaking", "Critical thinking", "Mentoring" ], "hardSkills" : [ { "name" : "Qualitative analysis", "level" : "intermediate" }, { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Digital data analysis", "level" : "intermediate" }, { "name" : "Research methods", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Reporting", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Negotiation" }, { "name" : "Conflict resolution" }, { "name" : "Public speaking" }, { "name" : "Critical thinking" }, { "name" : "Mentoring" } ], "majorSkills" : "Applied research, Monitoring and evaluation, Data analysis, Reporting", "majorSkillsList" : [ "Applied research", "Monitoring and evaluation", "Data analysis", "Reporting" ], "coreResponsibilities" : "Write requests for proposals, Write Terms of Reference, Review research tools, Advise on sampling strategies, Advise on methodologies, Review analysis, Review reporting, Support quality assurance during fieldwork, Conduct on-site visits, Provide technical expertise to research projects, Provide technical expertise to M&E projects, Advise on fit-for-purpose designs, Suggest qualitative methodologies, Suggest quantitative methodologies, Suggest other research approaches, Ensure ethical standards are upheld, Ensure safeguarding standards are upheld, Ensure field implementation is conducted to high standards, Train field research partners, Oversee field research partners, Ensure research outputs are accessible, Ensure research outputs are understandable, Ensure research outputs are useful, Utilise research outputs, Develop research partnerships, Maximise opportunities for cost-sharing, Maximise opportunities for joint learning, Deliver other duties relevant to position", "teamCollaboration" : "Work across functions; Work across countries; Work alongside global MERL team", "projectManagementSkills" : [ "Project management", "Research processes", "Research timelines" ], "domainKnowledge" : "Gender; Sexual reproductive health; Mental health; Economic empowerment", "domainList" : [ "gender", "sexual-reproductive-health", "mental-health", "economic-empowerment" ], "domainSpecificKnowledge" : [ "Gender", "Sexual reproductive health", "Mental health", "Economic empowerment" ], "communicationSkills" : "Knowledge management communication; Engaging reports; Research outputs communication", "documentationSkills" : "Reporting; Research outputs", "innovationCreativity" : "Creative mindset", "problemSolvingSkills" : "Uncovering new insights; Translating insights", "specialRequirements" : "12 month contract basis", "qualificationsBasic" : "Minimum 5 years applied research, Minimum 4 years M&E experience, Postgraduate degree in relevant field, SQL proficiency, Qualitative and quantitative research design, Fieldwork experience, Data analysis experience, Reporting experience, Commissioning research agencies, Managing research agencies, Qualitative data analysis, Quantitative data analysis, Digital adaptations data analysis, Uncovering new insights, Translating insights into reports, Strategic planning experience, Knowledge management experience, Communication skills, Organisation skills, Project management skills, Cultural awareness, Sensitivity to cultures, Creative mindset, Inquisitive mindset, Fluent in English, High level English writing, High level English speaking", "qualificationsPreferred" : "Experience with girls on sensitive issues, Experience with participatory engagement, Technical knowledge in thematic areas, Background evaluating programs for women/girls, Hands-on applied research experience, Experience training others in research methods, Experience mentoring others in research methods, Experience training others in data analysis, Experience mentoring others in data analysis, Experience training others in reporting, Experience mentoring others in reporting", "remoteFriendly" : true, "rawDescription" : "Who we are Girl Effect is an international non-profit that builds media that girls want, trust and need. From chat-bots to chat-shows and TV dramas to tech, our content is reaching millions of girls in Africa and Asia to make choices and changes in their lives. Igniting their confidence to act differently at a time that can define their future. We create safe spaces for girls, sharing facts, and answering questions about health, nutrition, education, relationships and so much more. And we use innovative technology so we can reach girls at scale. We arm girls with the skills to negotiate and redefine what they are told is possible, so every girl can choose to be in control of her body, her health, her learning and livelihood. When a girl unlocks her power to make different choices that change her life, it inspires others to do so too. She starts a ripple effect that impacts her family, her community, her country. That’s the Girl Effect. Role Context The Evidence write requests for proposals and Terms of Reference for studies, review research tools, advise on sampling strategies and methodologies, and review analysis and reporting. Support with quality assurance during fieldwork, with on-site visits' or something, as I think this will be a key aspect of the role. Provide technical expertise to research, monitoring, and evaluation projects, working alongside our global MERL team as required. You will advise on fit-for purpose designs suggesting qualitative and/or quantitative methodologies or other approaches (e. g. using digital methods or secondary data sources) as appropriate. Ensure that Girl Effect’s ethical and safeguarding standards are upheld, and that field implementation is conducted to the highest standards, through training and oversight of field research partners. Ensure that research outputs are accessible, readily understandable, and useful, ensuring they are utilised as much as possible. Develop research partnerships with local and international research organisations to maximise opportunities for cost-sharing and joint learning. This list should not be considered exhaustive; you will be expected to deliver other duties relevant and appropriate to this position. Who You Are (Experience Required) Substantial experience (minimum 5 years) in applied research and/or monitoring and evaluation in Kenya or a postgraduate degree in a relevant field and at least 4 years of work experience. Passionate about working with adolescent girls and young women and truly supporting them thrive in challenging environments. Demonstrated experience in implementation of high quality qualitative and quantitative research design, fieldwork, data analysis and reporting. Experience of commissioning and managing research agencies throughout projects ensuring deliverables are completed on time and meeting the organisational needs. Strong qualitative and quantitative data analysis skills; proficient with digital adaptations. Demonstrated experience in uncovering new insights and translating these into exciting, engaging reports and research outputs. Experience in strategic planning and knowledge management Strong communication skills; able to work effectively across functions and countries. Excellent organisation and project management skills; able to develop and drive research processes and timelines. Strong cultural awareness and sensitivity about the cultures within which Girl Effect operates. Creative and inquisitive mindset with strong communication and organisational skills. Commitment to realising the potential of girls and to the vision and values of Girl Effect. Desirable Expertise working with girls on sensitive issues in Kenya Experience with participatory engagement approaches Technical/theoretical knowledge in one or more of Girl Effect’s thematic areas (e. g. gender, sexual and reproductive health, mental health, or economic empowerment) Background in evaluating programmes that relate to women and girls Hands-on experience of applied research in emerging markets or developing contexts. Experience in training and mentoring others in research methods, data analysis and reporting. Fluent in English, with a high level in writing as well as speaking What Else You Should Know As we continue to scale and grow - we are hugely ambitious for our future and we are looking for people who are driven to change the world for girls. Our teams are a diverse mix across sectors (non-profit and commercial) and specialisms (from Creative through to Gender and Insight). You’ll learn and grow in an environment that will challenge you to think and work with a fresh perspective. In turn, you can expect to work somewhere where you will be stretched and developed in your role, a place where you can build your career and work with talented, engaged people committed to our cause. Girl Effect is committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, or gender identity or expression. We are proud to be an equal opportunity workplace. We are committed to building an organisation that is increasingly representative of the communities that we serve. To this end, due regard will be paid to recruiting candidates with diverse professional, academic and cultural backgrounds. Furthermore, Girl Effect is committed to safeguarding and promoting the welfare and rights of all individuals, particularly the adolescent girls and young women we support. We have zero-tolerance for safeguarding violations, including sexual exploitation, abuse, and harassment (SEAH). All employees are required to adhere to our safeguarding policies and successfully complete relevant background checks, including reference and criminal record checks where applicable. This role is subject to a standard background disclosure. This role is being recruited for on a 12 month contract basis. Only applications submitted via https://job-boards.greenhouse.io/girleffect will be reviewed. Application closing date –29th June 2026", "summaryDescription" : "Evidence and Insights Manager at Girl Effect. Skills: Applied research, Monitoring and evaluation, Data analysis, Reporting. Write requests for proposals. Write Terms of Reference", "postedDate" : "2026-06-15T23:29:34.800", "createdAt" : "2026-06-15T23:29:34.800", "lastUpdated" : "2026-06-16T06:58:42.744", "ingestTimestamp" : "2026-06-15T23:29:34.800", "mongoId" : "6a306724f292fd229cfb9ac9", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Qualitative analysis", "Quantitative analysis", "Digital data analysis", "Research methods", "Data analysis", "Reporting", "Leadership", "Negotiation", "Conflict resolution", "Public speaking", "Critical thinking", "Mentoring", "Applied research", "Monitoring and evaluation", "Research design", "Fieldwork", "Commissioning research", "Managing research", "Strategic planning", "Knowledge management", "Project management", "Research processes", "Research timelines", "Gender", "Sexual reproductive health", "Mental health", "Economic empowerment" ], "skillCount" : 27, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Non-Profit", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305b67f292fd229cf5d4fc", "title" : "Director, Insights and Analytics", "company" : "Dyne Therapeutics", "industry" : "Biotech", "salary" : { "min" : 190000.0, "max" : 240000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Waltham, Massachusetts, United States", "locations" : [ "Waltham", "Massachusetts", "United States" ], "timestamp" : "2026-06-16T08:31:17.425", "fingerprint" : "59f22a5765c588850e3ab8950630ad9bde5cc8895614c342afcde66b49a10ae1", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/dynetherapeutics/jobs/6020363004", "externalId" : "6020363004", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Waltham", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3762385,-71.2355644" } ], "locationText" : "Waltham, Massachusetts, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "Python, R, SQL, JMP, Spotfire", "professionalSkills" : [ "Statistical analysis", "Data analysis", "Data visualization" ], "hardSkillsList" : [ "Statistical modeling", "Experimental design" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Experimental design", "level" : "intermediate" } ], "majorSkills" : "Statistical modeling, Data analysis", "majorSkillsList" : [ "Statistical modeling", "Data analysis" ], "coreResponsibilities" : "Analyze experimental data, Develop statistical models, Design experiments, Generate reports, Communicate findings", "teamCollaboration" : "Research and Development teams; Cross-functional teams", "domainKnowledge" : "Biotechnology; Drug discovery", "domainList" : [ "biotechnology", "drug-discovery" ], "domainSpecificKnowledge" : [ "Biotechnology", "Drug discovery" ], "toolProficiency" : [ "JMP", "Spotfire", "R", "Python", "SQL" ], "communicationSkills" : "Written reports; Oral presentations", "documentationSkills" : "Technical documentation", "problemSolvingSkills" : "Data interpretation; Troubleshooting", "qualificationsBasic" : "5+ years experience, Bachelor's degree", "qualificationsPreferred" : "Master's degree preferred, PhD preferred", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Company Overview: Dyne Therapeutics is focused on delivering functional improvement for people living with genetically driven neuromuscular diseases. We are developing therapeutics that target muscle and the central nervous system (CNS) to address the root cause of disease. The company is advancing clinical programs for Duchenne muscular dystrophy (DMD) and myotonic dystrophy type 1 (DM1) as well as a preclinical programs for facioscapulohumeral muscular dystrophy (FSHD) and Pompe disease. At Dyne, we are on a mission to deliver functional improvement for individuals, families and communities. Learn more at https://www.dyne-tx.com/, and follow us on X, LinkedIn and Facebook. Role Summary: The Director, Insights and Analytics leads the generation of actionable market, customer, and data-driven insights to inform commercial strategy and execution across Dyne’s portfolio of assets in clinical development for rare neuromuscular diseases. This role integrates forecasting, market research, competitive intelligence, and advanced analytics to shape strategic decisions, optimize go-to-market planning, and enable organizational alignment. The Director serves as a strategic partner across cross-functional teams, translating complex data into clear, impactful recommendations that drive business outcomes. This role is based in Waltham, MA. Primary Responsibilities Include: Forecasting and Strategic Planning Lead development of long-range global forecasting models and scenario planning tools to project product uptake, access, and revenue Evaluate and enhance forecasting methodologies to improve accuracy, scalability, and agility Synthesize inputs across multiple data sources (e.g., market research, competitive intelligence, analogs) to validate assumptions and inform projections Support long-range planning, lifecycle management, and commercial assessments for pipeline and business development opportunities Partner with commercial operations and finance to guide operational forecasting and annual planning processes (AOP/budgeting) Serve as a strategic advisor to cross-functional stakeholders across Brand, Market Access, Finance, Supply, Trade, and IT Market Research and Insights Generation Design and execute global insights generation plans leveraging primary and secondary market research Manage end-to-end market research processes, including RFP development, vendor selection, and project execution Translate research findings into clear, actionable insights and strategic recommendations for senior leadership Ensure all research activities comply with data governance, privacy standards, and relevant external engagement policies Build strong partnerships with internal stakeholders to align insights with business priorities Competitive Intelligence Lead competitive intelligence strategy and analysis for key therapeutic areas, assessing market dynamics and competitive positioning Oversee execution of competitive intelligence activities, including monitoring, reporting, ad hoc analyses, and congress intelligence Deliver timely, actionable insights to inform go-to-market strategies, product development, and positioning Develop executive-ready materials and briefings to support leadership decision-making Represent the organization as the primary point of contact for competitive intelligence and at key congresses Commercial Data Analytics and Capability Building Expand and optimize the organization’s data ecosystem, including evaluation and integration of new data sources and tools Lead development of dashboards, KPIs, and performance tracking frameworks to enable data-driven decision-making Apply advanced analytics, statistical modeling, and trend analysis to generate insights from internal and external data Translate complex data into compelling narratives and recommendations that influence business action Educate stakeholders on data tools, dashboards, and data literacy to drive adoption and impact Ensure adherence to data governance, compliance, and privacy standards Education and Skills Requirements: Bachelor’s degree required; advanced degree (MBA, PhD, PharmD) preferred 10+ years of experience in forecasting, market research, competitive intelligence, and/or data analytics within biotech or pharmaceutical environments Experience supporting product launches and/or rare disease markets preferred Strong understanding of regulatory and compliance considerations related to market research and data usage in pharma/biotech Demonstrated ability to synthesize complex data and communicate insights clearly to diverse audiences, including senior leadership Exceptional data storytelling skills with expertise in translating insights into impactful presentations and recommendations Proven ability to lead through influence in a cross-functional, matrixed environment Experience managing external vendors, including negotiation, scope management, and performance oversight Strong business acumen with the ability to connect insights to strategic and operational decisions Ability to operate effectively in a fast-paced, dynamic environment while managing multiple priorities Demonstrates high standards of professionalism, integrity, and accountability #LI-Onsite MA Pay Range $190,000—$240,000 USD The pay range reflects the base pay range Dyne reasonably expects to pay for this role at the time of posting. Individual compensation depends on factors such as education, experience, job-related knowledge, and demonstrated skills. The statements contained herein reflect general details as necessary to describe the principles functions for this job, the level of knowledge and skill typically required, and the scope of responsibility, but should not be considered an all-inclusive listing of work requirements. Individuals may perform other duties as assigned, including work in other functional areas to cover absences or relief, to equalize peak work periods or otherwise balance workload. Dyne Therapeutics is an equal opportunity employer and will not discriminate against any employee or applicant on the basis of age, color, disability, gender, national origin, race, religion, sexual orientation, veteran status, or any classification protected by federal, state, or local law.", "summaryDescription" : "Director, Insights and Analytics at Dyne Therapeutics. Skills: Statistical modeling, Data analysis. Analyze experimental data. Develop statistical models", "postedDate" : "2026-06-15T23:23:00.223", "createdAt" : "2026-06-15T23:23:00.223", "lastUpdated" : "2026-06-16T08:31:17.425", "ingestTimestamp" : "2026-06-15T23:23:00.223", "mongoId" : "6a305b67f292fd229cf5d4fc", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 190000, "salaryAnnualMax" : 240000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical modeling", "Experimental design", "Data analysis", "Statistical analysis", "Data visualization", "Biotechnology", "Drug discovery", "JMP", "Spotfire", "R", "Python", "SQL" ], "skillCount" : 12, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Director", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2a660d74d8ee00a062bbdc", "title" : "AI & AWS Software Development Engineer, Ringlink CS Technology Enablement", "company" : "Amazon.com Services LLC", "industry" : "Software Development, alexa and amazon devices", "salary" : { "min" : 143700.0, "max" : 194400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Hawthorne, California, USA", "locations" : [ "Hawthorne, California, USA" ], "timestamp" : "2026-06-15T02:15:14.939", "fingerprint" : "ebfae8ff34241fc394202aa82bfacdf81f79e0ee17b79e7070fa5b61797ad5d7", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10442313/apply", "externalId" : "1fa5fafd-24fb-4318-8fdb-c01005472de4", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hawthorne", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "33.9128272,-118.3426122" } ], "locationText" : "Hawthorne, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AWS, Bedrock, Amazon Q, SageMaker, Comprehend, Lex, Polly, Transcribe, Amazon Connect, Contact Lens, Customer Profiles, Evaluations, EC2, ECS, Fargate, Lambda, VPC, IAM, CloudFormation, Python, Machine Learning, Natural Language Processing", "professionalSkills" : [ "AI Strategy", "Technical Leadership", "Infrastructure Management", "Platform Management", "Cross-Functional Collaboration", "Security Architecture", "Risk Management", "Thought Leadership", "Code Quality" ], "hardSkillsList" : [ "System performance optimization", "Cost optimization", "Failover management", "Data replication", "Scaling bottlenecks", "Latency management", "Security controls", "Code reviews" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "System performance optimization", "level" : "intermediate" }, { "name" : "Cost optimization", "level" : "intermediate" }, { "name" : "Failover management", "level" : "intermediate" }, { "name" : "Data replication", "level" : "intermediate" }, { "name" : "Scaling bottlenecks", "level" : "intermediate" }, { "name" : "Latency management", "level" : "intermediate" }, { "name" : "Security controls", "level" : "intermediate" }, { "name" : "Code reviews", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "AI/ML, AWS, Amazon Connect, Software Development", "majorSkillsList" : [ "AI/ML", "AWS", "Amazon Connect", "Software Development" ], "coreResponsibilities" : "Research and evaluate AWS AI services, Leverage Amazon Connect AI capabilities, Determine adoption of AI technologies, Assess impact of AI technologies, Create proof of concepts, Create pilot programs, Collaborate with data science teams, Productionize ML models, Manage ML model lifecycle, Drive AI model performance optimization, Monitor AI model performance, Perform A/B testing, Improve AI models continuously, Own technical design, Own implementation of features, Deploy features to production, Lead technical discussions, Lead design reviews, Build scalable solutions, Build secure solutions, Build reliable solutions, Build cost-optimized solutions, Integrate AWS compute services, Integrate core AWS offerings, Integrate AI technologies, Lead CS in leveraging Amazon Connect, Replace custom coded solutions, Define integration architecture, Define service definitions, Balance customer needs, Balance technical constraints, Deliver optimal solutions, Build customer support automation solutions, Handle millions of interactions, Achieve sub-second response times, Drive continuous improvements, Improve development processes, Improve deployment processes, Implement automated testing, Implement monitoring, Implement deployment pipelines, Ensure high quality, Ensure reliability, Implement comprehensive testing strategies, Monitor system performance, Manage proactive system health, Optimize system performance, Optimize system costs, Utilize resources efficiently, Improve architecture across AWS, Monitor AWS infrastructure framework, Manage AWS roles, Manage AWS keys, Manage AWS permissions, Manage AWS exceptions, Manage AWS scaling, Manage AWS patches, Lead evaluation for failover, Lead evaluation for recovery, Lead evaluation for data replication, Lead evaluation for scaling bottlenecks, Lead evaluation for latency, Lead evaluation for security, Maximize Ring & Blink CS ROI, Minimize cost, Optimize architecture, Work with product teams, Work with business teams, Maintain current state architecture artifacts, Build target state architectures, Advise program management, Identify technology dependencies, Identify external dependencies, Build work-back plans, Lead collaboration across diverse groups, Ensure CS is securing neighbor data, Adhere to Amazon's standards, Work with Security teams, Work with Privacy teams, Get directional buy-ins, Design security architecture, Design security controls, Ensure compliance with regulations, Implement security best practices, Conduct code reviews, Provide technical mentoring, Elevate team capabilities, Maintain high code quality, Create reusable solutions, Create reference architectures, Lead development of technical content, Lead delivery of technical content, Mentor others, Develop others, Share lessons learned, Share best practices, Participate in on-call rotations, Ensure system reliability, Ensure rapid incident response, Design core features, Build core features, Integrate AI technologies, Integrate customer support infrastructure, Leverage AWS offerings, Build robust solutions, Scale solutions, Automate customer support, Handle millions of interactions, Achieve sub-second response times, Drive technical improvements, Optimize AI systems, Optimize model performance", "teamCollaboration" : "Cross-functional teams; Diverse groups; Engineering teams; Product teams; Security teams; Privacy teams; Legal teams; Operations teams", "projectManagementSkills" : [ "Work-back plans" ], "domainKnowledge" : "Customer service applications; AI-driven automations; ML model lifecycle; AWS compute services; Amazon Connect; Contact center regulations; Data privacy requirements; AI/ML systems; Large language models; Prompt engineering; RAG systems; Model fine-tuning; AWS AI services; Amazon Connect AI; Real-time systems; Low-latency requirements; Customer-facing applications; Voice communications", "domainList" : [ "customer-service-applications", "ai-driven-automations", "ml-model-lifecycle", "aws-compute-services", "amazon-connect", "contact-center-regulations", "data-privacy-requirements", "ai-ml-systems", "large-language-models", "prompt-engineering", "rag-systems", "model-fine-tuning", "aws-ai-services", "amazon-connect-ai", "real-time-systems", "low-latency-requirements", "customer-facing-applications", "voice-communications" ], "domainSpecificKnowledge" : [ "Customer service applications", "AI-driven automations", "ML model lifecycle", "AWS compute services", "Amazon Connect", "Contact center regulations", "Data privacy requirements", "AI/ML systems", "Large language models", "Prompt engineering", "RAG systems", "Model fine-tuning", "AWS AI services", "Amazon Connect AI", "Real-time systems", "Low-latency requirements", "Customer-facing applications", "Voice communications" ], "toolProficiency" : [ "AWS", "Amazon Connect" ], "communicationSkills" : "Technical presentations; Technical content", "documentationSkills" : "Architecture artifacts; Service definitions; Technical content", "innovationCreativity" : "AI initiatives; Innovative AI solutions; Emerging AI technologies", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; System health management; Performance monitoring; Cost optimization", "specialRequirements" : "On-call rotations", "outcomesObjectives" : "Improve efficiency; Set new standards; Provide measurable business value; Handle millions of interactions; Achieve sub-second response times; Maximize ROI; Minimize cost; Ensure system reliability; Ensure rapid incident response", "qualificationsBasic" : "5+ years experience, Experience with AWS AI services, Production deployment experience, Deep knowledge of Amazon Connect AI, Experience building ML/AI systems, Model monitoring experience, A/B testing experience, Performance optimization experience, Expertise with AWS compute optimization, Experience with auto-scaling, Experience with load balancing, Experience with cost optimization, Experience with real-time systems, Experience with low-latency requirements", "qualificationsPreferred" : "Experience with prompt engineering, Experience with RAG systems, Experience with model fine-tuning", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Ring and Blink Customer Service Engineering Services team is transforming how we serve thousands of customers through innovative AI solutions. Our team is building the future of customer service, developing intelligent systems that provide timely, proactive support while improving efficiency. We're looking for an experienced Software Development Engineer to design and deliver key components of our AI initiatives. In this role, you'll design and implement critical features of our AI-powered customer service platform, make key architectural decisions, and help define technical approaches for automated support systems. You'll work across teams to develop scalable solutions that set new standards for AI-powered customer service. Key job responsibilities AI/ML Strategy & Innovation · Research and evaluate AWS AI services (Bedrock, Amazon Q, SageMaker, Comprehend, Lex, Polly, Transcribe) and Amazon Connect AI features for customer service applications · Leverage Amazon Connect's AI capabilities including Contact Lens, Customer Profiles, Evaluations, and QinC to build intelligent customer service solutions · Determine when to adopt emerging AI technologies and assess their impact on current and future solutions, including integration with existing systems · Create proof of concepts and pilot programs to promote AI-driven automations and optimizations for technology and business processes · Collaborate with data science teams to productionize ML models and ensure smooth model lifecycle management using AWS compute infrastructure · Drive AI model performance optimization, including monitoring, A/B testing, and continuous improvement initiatives Technical Leadership · Own end-to-end technical design and implementation of major features within our AI initiatives and AWS infrastructure, from initial concept through production deployment · Lead technical discussions and design reviews for new features, ensuring alignment with business objectives and technical constraints · Build scalable, secure, reliable, and cost-optimized solutions that integrate AWS compute services (EC2, ECS, Fargate, Lambda) and core offerings (VPC, IAM, CloudFormation) with AI technologies · Lead CS in leveraging Amazon Connect native offerings to replace custom coded solutions where appropriate · Define integration architecture and service definitions for interactions between systems · Balance customer needs with technical constraints to deliver optimal solutions that provide measurable business value Infrastructure & Platform Management · Build robust, scalable solutions for customer support automation that handle millions of interactions with sub-second response times · Drive continuous improvements in development and deployment processes, including automated testing, monitoring, and deployment pipelines using AWS core services · Ensure high quality and reliability through comprehensive testing strategies, performance monitoring, and proactive system health management · Optimize system performance and costs through efficient resource utilization and architectural improvements across AWS services · Monitor and manage AWS infrastructure framework services, roles, keys, permissions, exceptions, scaling, and patches · Lead the evaluation and architecture to manage failover and recovery, data replication, scaling bottlenecks, latency, and security · Maximize Ring & Blink CS's ROI while minimizing cost through architectural optimization using both 1P and 3P systems Cross-Functional Collaboration & Influence · Work with product and business teams to maintain current state architecture artifacts and build target state architectures for the product roadmap · Advise program management on technology/external dependencies for delivering new feature requests and help build work-back plans · Lead collaboration across diverse groups including engineering, product, security, privacy, legal, and operations teams · Present technical solutions and recommendations to senior leadership and technical stakeholders Security, Compliance & Risk Management · Ensure CS is securing neighbor data by adhering to Amazon's security, privacy, legal, and operational standards · Work with Security and Privacy teams on getting directional buy-ins for solutions · Design security architecture and controls for AI/ML systems, ensuring compliance with contact center regulations (PCI DSS, HIPAA) and data privacy requirements · Implement security best practices for customer-facing AI applications and voice communications Thought Leadership & Development · Conduct code reviews and provide technical mentoring to elevate team capabilities and maintain high code quality standards · Create reusable solutions and reference architectures that other engineers and Solutions Architects can leverage · Lead the development and delivery of technical content (white papers, workshops, presentations, sample code) · Actively mentor and develop others, sharing lessons learned and best practices · Participate in on-call rotations to ensure system reliability and rapid incident response A day in the life As an Engineer on this team, your day revolves around shaping the future of customer service: · Design & Build: Implement core features of our AI-powered customer service platforms using cutting-edge machine learning and natural language processing technologies · Architect: Make critical architectural decisions that enable seamless integration of AI technologies with existing customer support infrastructure leveraging AWS offerings · Scale: Build robust, scalable solutions for customer support automation using Amazon Connect and its AI capabilities that handle millions of interactions with sub-second response times · Optimize: Drive technical improvements across our AI systems including model performance optimization, cost reduction, and reliability enhancements using AWS core offerings · Collaborate: Guide and work with cross-functional teams including data scientists, product managers, and UX designers to promote engineering best practices · Support: Participate in on-call rotations to ensure system reliability and rapid incident response · Mentor: Conduct code reviews and provide technical mentoring to elevate team capabilities and maintain high code quality standards About the team The Ring and Blink CS Tech team owns and manages the customer support technology stack to provide and empower Ring's & Blink's customer support associates to deliver exceptional service to our Neighbors (customers). Our vision is to be customer-inspired and technology-enabled to propel customer service towards new horizons, transforming it into a scalable, secure, enterprise-grade infrastructure powered by AI and automation. We're evolving from reactive customer service to proactive, AI-enhanced support experiences. We are committed to delivering neighbor and associate experiences that are unparalleled, simplifying and streamlining business processes with intuitive interfaces via out-of-the-box, low-code, and innovative AI solutions. We focus on providing a seamless and effortless experience that revolutionizes customer service and boosts productivity. Basic Qualifications: - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of software development engineer or related occupational experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - Experience programming with at least one software programming language - Experience managing a team of high calibre Software Engineers developing complex, world class, scalable software systems that have been successfully delivered to customers Preferred Qualifications: - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - · Experience with Generative AI technologies and large language models including prompt engineering, RAG systems, and model fine-tuning - · Strong background in AWS AI services such as Amazon Bedrock, SageMaker, Comprehend, Lex, Polly, and Transcribe with production deployment experience - · Deep knowledge of Amazon Connect AI capabilities - · Experience building and maintaining production ML/AI systems including model monitoring, A/B testing, and performance optimization - · Expertise with AWS compute optimization including auto-scaling, load balancing, and cost optimization strategies - · Experience with real-time systems and low-latency requirements for customer-facing applications and voice communications Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Hawthorne - 143,700.00 - 194,400.00 USD annually", "summaryDescription" : "AI & AWS Software Development Engineer, Ringlink CS Technology Enablement at Amazon.com Services LLC. Skills: AI/ML, AWS, Amazon Connect, Software Development. Research and evaluate AWS AI services. Leverage Amazon Connect AI capabilities", "postedDate" : "2026-06-13T11:32:53.605", "createdAt" : "2026-06-13T11:32:53.605", "lastUpdated" : "2026-06-15T02:15:14.939", "ingestTimestamp" : "2026-06-13T11:32:53.605", "mongoId" : "6a2a660d74d8ee00a062bbdc", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10442313/apply", "salaryAnnualMin" : 143700, "salaryAnnualMax" : 194400, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "System performance optimization", "Cost optimization", "Failover management", "Data replication", "Scaling bottlenecks", "Latency management", "Security controls", "Code reviews", "Mentoring", "AI/ML", "AWS", "Amazon Connect", "Software Development", "AI Strategy", "Technical Leadership", "Infrastructure Management", "Platform Management", "Cross-Functional Collaboration", "Security Architecture", "Risk Management", "Thought Leadership", "Code Quality", "Work-back plans", "Customer service applications", "AI-driven automations", "ML model lifecycle", "AWS compute services", "Contact center regulations", "Data privacy requirements", "AI/ML systems", "Large language models", "Prompt engineering", "RAG systems", "Model fine-tuning", "AWS AI services", "Amazon Connect AI", "Real-time systems", "Low-latency requirements", "Customer-facing applications", "Voice communications" ], "skillCount" : 40, "jobCategory" : "engineering", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2ca57974d8ee00a09b6af7", "title" : "Engineering Lead - Insurance (Data & AI)", "company" : "Alpha Financial Markets Consulting", "industry" : "Consulting", "salary" : { "min" : 115000.0, "max" : 165000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Lead Engineering role in Edinburgh, UK, adjusted for the consulting industry and company size." }, "location" : "Edinburgh, City Of Edinburgh, Scotland, United Kingdom", "locations" : [ "Edinburgh", "City Of Edinburgh", "Scotland", "United Kingdom", "London", "Greater London", "England", "United Kingdom" ], "certifications" : [ "Industry conferences", "Certifications", "Training programmes" ], "timestamp" : "2026-06-15T21:23:57.860", "fingerprint" : "9d78e5f01dd0c79000adf95a70818c57aceedd25e88c53954e48c11de4a620e3", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/alphafmcroles/jobs/8587942002", "externalId" : "8587942002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Edinburgh", "state" : "City Of Edinburgh", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "55.9519018,-3.1904199" } ], "locationText" : "Edinburgh, City Of Edinburgh, United Kingdom", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "REST, GraphQL, Kubernetes, Terraform, GitHub Actions, Azure DevOps, Jenkins, Kafka, Event streaming, EDI, ACORD XML, JSON", "professionalSkills" : [ "System design", "Integration patterns", "Stakeholder management", "Contract negotiation", "Risk management" ], "hardSkillsList" : [ "Data engineering", "AI/ML", "DevOps", "Cloud engineering", "Security engineering", "API development", "Data privacy engineering", "Secure SDLC" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "AI/ML", "level" : "intermediate" }, { "name" : "DevOps", "level" : "intermediate" }, { "name" : "Cloud engineering", "level" : "intermediate" }, { "name" : "Security engineering", "level" : "intermediate" }, { "name" : "API development", "level" : "intermediate" }, { "name" : "Data privacy engineering", "level" : "intermediate" }, { "name" : "Secure SDLC", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data & AI, Insurance domain, Engineering leadership", "majorSkillsList" : [ "Data & AI", "Insurance domain", "Engineering leadership" ], "coreResponsibilities" : "Prioritise remediation, Balance feature delivery, Evaluate third-party software, Recommend third-party software, Shape technical solutions, Meet regulatory requirements, Meet operational requirements, Oversee delivery of capabilities, Ensure compliance with standards, Ensure compliance with regulations, Act as subject matter expert, Bridge business and engineering, Accountable for quality, Accountable for timeliness, Accountable for technical integrity, Champion Agile, Champion DevSecOps, Contribute to sprint planning, Contribute to backlog refinement, Contribute to release governance, Define engineering KPIs, Track engineering KPIs, Manage stakeholder expectations, Provide transparent reporting, Lead procurement, Lead contract negotiations, Represent engineering function, Attend senior leadership forums, Attend architecture boards, Attend client-facing engagements", "teamCollaboration" : "Business stakeholders; Engineering teams; Cross-functional teams; Senior leadership forums; Architecture boards", "projectManagementSkills" : [ "Agile", "DevSecOps", "Sprint planning", "Backlog refinement", "Release governance" ], "domainKnowledge" : "Insurance business processes; Policy lifecycle management; Claims handling; Bordereaux processing; Reinsurance ceding; Premium calculation engines; Solvency II; FCA requirements; GDPR; ACORD XML; JSON standards", "domainList" : [ "insurance-business-processes", "policy-lifecycle-management", "claims-handling", "bordereaux-processing", "reinsurance-ceding", "premium-calculation-engines", "solvency-ii", "fca-requirements", "gdpr", "acord-xml", "json-standards" ], "domainSpecificKnowledge" : [ "Insurance business processes", "Policy lifecycle management", "Claims handling", "Bordereaux processing", "Reinsurance ceding", "Premium calculation engines", "Solvency II", "FCA requirements", "GDPR", "ACORD XML", "JSON standards" ], "toolProficiency" : [ "Guidewire", "Duck Creek", "Majesco" ], "communicationSkills" : "Transparent reporting; Client-facing engagements", "continuousLearning" : "Continuous learning budget; Industry conferences; Certifications; Training programmes", "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "outcomesObjectives" : "Improve quality; Improve timeliness; Improve technical integrity; Track lead time; Track deployment frequency; Track MTTR; Track defect escape rate", "qualificationsBasic" : "5+ years experience in insurance domain, Experience with insurance business processes, Experience with policy lifecycle management, Experience with claims handling, Experience with bordereaux processing, Experience with reinsurance ceding, Experience with premium calculation engines, Experience with Solvency II, Experience with FCA requirements, Experience with market standards, Experience with GDPR", "qualificationsPreferred" : "Experience with Guidewire, Experience with Duck Creek, Experience with Majesco", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Alpha Financial Markets Consulting (Alpha) is a leading global consultancy to the financial services industry. We are a boutique management consulting firm that offers the world’s top industry players a competitive edge through our expertise and industry insight. Our team is of a uniquely high calibre and by focusing across the General Insurance prioritise remediation in balance with feature delivery. Evaluate and recommend third-party insurance software (e. g. Guidewire, Duck Creek, Majesco) and integration patterns. Insurance Domain Delivery Apply specialist knowledge of insurance business processes to shape technical solutions that meet regulatory and operational requirements. Oversee delivery of insurance-specific capabilities: policy lifecycle management, claims handling, bordereaux processing, reinsurance ceding, and premium calculation engines. Ensure compliance with industry standards and regulations including Solvency II, FCA requirements, market standards, and GDPR. Act as a subject matter expert (SME) bridging business stakeholders and engineering teams on insurance domain requirements. Delivery accountable for quality, timeliness, and technical integrity. Champion Agile and DevSecOps practices; contribute to sprint planning, backlog refinement, and release governance. Define and track engineering KPIs including lead time, deployment frequency, MTTR, and defect escape rate. Manage stakeholder expectations and provide transparent reporting on engineering progress and risk. Stakeholder lead procurement and contract negotiations where required. Represent the engineering function in senior leadership forums, architecture boards, and client-facing engagements. Skills REST and GraphQL APIs. Cloud & Infrastructure: Kubernetes, Terraform, CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins). Data & Integration: Kafka / event streaming, enterprise integration patterns, EDI/ACORD XML or JSON standards. Security & Compliance: OWASP practices, data privacy engineering, secure SDLC. What We Offer Competitive base salary benchmarked to senior tech consulting market rates. Annual performance bonus tied to individual and company outcomes. Comprehensive benefits package including private medical insurance, life assurance, and income protection. Hybrid working model with flexible arrangements to support work-life balance. Generous pension scheme with enhanced employer contributions. Continuous learning budget and access to industry conferences, certifications, and training programmes. 25 days annual leave plus bank holidays, with option to buy additional days. Employee assistance programme and wellbeing support.", "summaryDescription" : "Engineering Lead - Insurance (Data & AI) at Alpha Financial Markets Consulting. Skills: Data & AI, Insurance domain, Engineering leadership. Prioritise remediation. Balance feature delivery", "postedDate" : "2026-06-14T20:09:30.908", "createdAt" : "2026-06-14T20:09:30.908", "lastUpdated" : "2026-06-15T21:23:57.860", "ingestTimestamp" : "2026-06-14T20:09:30.908", "mongoId" : "6a2ca57974d8ee00a09b6af7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data engineering", "AI/ML", "DevOps", "Cloud engineering", "Security engineering", "API development", "Data privacy engineering", "Secure SDLC", "Leadership", "Data & AI", "Insurance domain", "Engineering leadership", "System design", "Integration patterns", "Stakeholder management", "Contract negotiation", "Risk management", "Agile", "DevSecOps", "Sprint planning", "Backlog refinement", "Release governance", "Insurance business processes", "Policy lifecycle management", "Claims handling", "Bordereaux processing", "Reinsurance ceding", "Premium calculation engines", "Solvency II", "FCA requirements", "GDPR", "ACORD XML", "JSON standards", "Industry conferences", "Certifications", "Training programmes", "Guidewire", "Duck Creek", "Majesco" ], "skillCount" : 39, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Lead", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Consulting", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2176ba74d8ee00a0c1ab40", "title" : "Sr. Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements", "company" : "Amazon Web Services, Inc.", "industry" : "Data Science, Data Engineering, Cloud Computing", "salary" : { "min" : 154600.0, "max" : 209100.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T02:43:46.876", "fingerprint" : "c76a879dbeb4f0eeb72cf66e4c547429421b00054afd935d73d1f1a16fec4b89", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10439451/apply", "externalId" : "fc4812aa-f855-45de-94e4-9841e411fe26", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AWS, GenAI, LLM, Python, Java, Scala, NodeJS, Hadoop, Hive, Spark, EMR", "professionalSkills" : [ "Data modeling", "Data warehousing", "ETL pipeline development", "Data architecture", "Data transformation", "Data quality", "Data pipelines", "Feature stores", "Data products" ], "hardSkillsList" : [ "Data engineering", "Data modeling", "Data warehousing", "ETL pipelines", "SQL", "Scripting language", "Programming language", "Data infrastructure", "Data models", "Data quality monitoring", "Data validation", "Data auditing", "Data pipelines", "LLM data pipelines", "Data products", "Feature stores", "GenAI applications" ], "hardSkills" : [ { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "ETL pipelines", "level" : "intermediate" }, { "name" : "SQL", "level" : "intermediate" }, { "name" : "Scripting language", "level" : "intermediate" }, { "name" : "Programming language", "level" : "intermediate" }, { "name" : "Data infrastructure", "level" : "intermediate" }, { "name" : "Data models", "level" : "intermediate" }, { "name" : "Data quality monitoring", "level" : "intermediate" }, { "name" : "Data validation", "level" : "intermediate" }, { "name" : "Data auditing", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "LLM data pipelines", "level" : "intermediate" }, { "name" : "Data products", "level" : "intermediate" }, { "name" : "Feature stores", "level" : "intermediate" }, { "name" : "GenAI applications", "level" : "intermediate" } ], "majorSkills" : "Data engineering, Data platform development, GenAI data solutions", "majorSkillsList" : [ "Data engineering", "Data platform development", "GenAI data solutions" ], "coreResponsibilities" : "Build backend data infrastructure, Maintain backend data infrastructure, Ensure data is clean, Ensure data is fresh, Optimize data for consumption, Lead architectural improvements, Simplify complex data systems, Simplify data transformations, Address data infrastructure deficiencies, Translate business problems to requirements, Partner with BIEs and product management, Define data products, Ensure data quality, Monitor data pipelines, Validate data pipelines, Audit data pipelines, Document data pipelines, Document data sources, Leverage AWS services, Leverage GenAI, Build next-generation data solutions, Improve efficiency, Unlock analytical capabilities, Build LLM data pipelines, Create data products for GenAI, Create feature stores for GenAI, Serve GenAI applications, Lead design reviews, Participate in design reviews", "teamCollaboration" : "Collaboration with Product Managers; Collaboration with BIEs; Collaboration with business partners; Partnering with stakeholders", "domainKnowledge" : "AWS services; GenAI; LLM", "domainList" : [ "aws-services", "genai", "llm" ], "domainSpecificKnowledge" : [ "AWS services", "GenAI", "LLM" ], "toolProficiency" : [ "AWS services", "GenAI" ], "communicationSkills" : "Business communication skills", "documentationSkills" : "Documentation of pipelines; Documentation of data sources", "innovationCreativity" : "Build next-generation data solutions; Unlock new analytical capabilities", "problemSolvingSkills" : "Translate business problem statements; Address deficiencies", "qualificationsBasic" : "5+ years data engineering, Data modeling experience, Warehousing experience, Building ETL pipelines, SQL experience, Python, Java, Scala, or NodeJS experience, Mentoring team members", "qualificationsPreferred" : "Big data technologies experience, Hadoop experience, Hive experience, Spark experience, EMR experience, Large data warehouses experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you passionate about leveraging data to deliver actionable insights that impact the daily business decisions of AWS? Do you want to have an impact on making strategic deals come to life? If so, we are looking for a Sr. Data Engineer to join the Strategic Customer Engagements team to develop a scalable data analytics platform. The Strategic Customer Engagements Deal Team works with our customers on commercial private pricing opportunities to meet their desired business outcomes while ensuring alignment with AWS business objectives. In this role, you will be responsible for end-to-end development of data engineering solutions from the ground up. You should have expertise in the creation and management of datasets and the proven ability to translate data into meaningful insights through collaboration with Product Managers, Business Intelligence Engineers (BIEs), and business partners. You should be passionate about designing scalable analytics solutions for a fast-growing business. This is a high-visibility role. The right candidate will possess excellent business and communication skills, be able to work with business owners to translate business problem statements into technical requirements. You should have a solid understanding of how to build efficient and scalable data infrastructure and data models. The role will leverage generative AI and AWS services to raise the bar on how the team consumes and acts on data and build the next generation of AI-enabled data platform. Key job responsibilities - Build and maintain backend data infrastructure for analytical platforms and applications, ensuring data is clean, fresh, and optimized for downstream consumption - Lead architectural improvements that simplify complex data systems and transformations and proactively address deficiencies that create bottlenecks in the data infrastructure - Translate business problem statements into technical data requirements, partnering with BIEs and product management and stakeholders to define what data products to build - Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources - Leverage AWS services and GenAI to build next-generation data solutions that improve efficiency and unlock new analytical capabilities - Build data pipelines purpose-built for LLM consumption and create data products and feature stores that serve GenAI applications in near real-time - Lead design reviews for your team's data architecture and actively participate in design reviews of related software and data systems Basic Qualifications: - 5+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience mentoring team members on best practices Preferred Qualifications: - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience operating large data warehouses Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 170,000.00 - 230,000.00 USD annually USA, VA, Arlington - 154,600.00 - 209,100.00 USD annually USA, WA, Seattle - 154,600.00 - 209,100.00 USD annually", "summaryDescription" : "Sr. Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements at Amazon Web Services, Inc.. Skills: Data engineering, Data platform development, GenAI data solutions. Build backend data infrastructure. Maintain backend data infrastructure", "postedDate" : "2026-06-13T05:06:17.324", "createdAt" : "2026-06-13T05:06:17.324", "lastUpdated" : "2026-06-15T02:43:46.876", "ingestTimestamp" : "2026-06-13T05:06:17.324", "mongoId" : "6a2176ba74d8ee00a0c1ab40", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10439451/apply", "salaryAnnualMin" : 154600, "salaryAnnualMax" : 209100, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data engineering", "Data modeling", "Data warehousing", "ETL pipelines", "SQL", "Scripting language", "Programming language", "Data infrastructure", "Data models", "Data quality monitoring", "Data validation", "Data auditing", "Data pipelines", "LLM data pipelines", "Data products", "Feature stores", "GenAI applications", "Data platform development", "GenAI data solutions", "ETL pipeline development", "Data architecture", "Data transformation", "Data quality", "AWS services", "GenAI", "LLM" ], "skillCount" : 26, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a3051f3f292fd229cf09724", "title" : "Senior AI Engineer, Product Engineering", "company" : "You.com", "industry" : "Technology", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior AI Engineer in New York, adjusted for company size and industry." }, "location" : "New York, New York, United States", "locations" : [ "New York", "New York", "United States", "San Francisco", "California", "United States", "United States - Remote" ], "timestamp" : "2026-06-16T10:37:22.892", "fingerprint" : "82208c56789d7df5cbd80853e585ea4ac24090b09d7bcc0bbd56b8744d6ce20b", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/youcom/jobs/5231873008", "externalId" : "5231873008", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, LLM, Search, Infrastructure", "professionalSkills" : [ "Product direction", "Solutions architecture", "Technical product spec", "Customer integration", "API design", "Developer experience" ], "hardSkillsList" : [ "Real-time retrieval", "LLM optimization" ], "hardSkills" : [ { "name" : "Real-time retrieval", "level" : "intermediate" }, { "name" : "LLM optimization", "level" : "intermediate" } ], "majorSkills" : "AI Search Infrastructure, LLM, API Product Management", "majorSkillsList" : [ "AI Search Infrastructure", "LLM", "API Product Management" ], "coreResponsibilities" : "Own API product direction, Define roadmap for core search APIs, Define roadmap for monitoring, Define roadmap for vertical feeds, Define roadmap for evaluation tooling, Define roadmap for new primitives, Lead solutions for strategic accounts, Architect customer integration, Unblock customer teams, Turn pilots into partnerships, Translate customer conversations into product bets, Write product specs, Prioritize roadmap, Become shipped features, Be technical face of product, Run technical deep-dives, Write docs, Write reference implementations, Show up in AI builder spaces, Set technical bar, Work with engineering on API design, Work with engineering on performance, Work with engineering on developer experience, Push back on poor quality, Ship code, Prototype new API primitives, Ship production code", "teamCollaboration" : "Partner with founders; Partner with engineering leaders; Work with engineering; Work with world-class talent", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "AI agent ecosystem; LLM ecosystem; Retrieval systems; Search infrastructure; Agent infrastructure; Vertical indexes; Large-scale infrastructure", "domainList" : [ "ai-agent-ecosystem", "llm-ecosystem", "retrieval-systems", "search-infrastructure", "agent-infrastructure", "vertical-indexes", "large-scale-infrastructure" ], "domainSpecificKnowledge" : [ "AI agent ecosystem", "LLM ecosystem", "Retrieval systems", "Search infrastructure", "Agent infrastructure", "Vertical indexes", "Large-scale infrastructure" ], "communicationSkills" : "Technical deep-dives; Write specs; Write docs; Write reference implementations; Pitching CTOs; Customer calls; Sales follow-up; Postmortem writing", "documentationSkills" : "Write docs; Write specs", "innovationCreativity" : "Prototype new API primitives", "problemSolvingSkills" : "Debugging integration; Unblock customer teams; Solve hard problems", "outcomesObjectives" : "Win high-value accounts; Deploy high-value accounts; Expand high-value accounts; Turn pilots into partnerships; Make AI systems reliable; Make AI systems transparent; Make AI systems useful", "qualificationsBasic" : "5+ years experience engineering/product, Significant time on developer-facing/API products, Can write production code, Deep familiarity AI agent/LLM ecosystem, Track record owning ambiguous problems end-to-end, Customer instincts, Excellent written/verbal communication, Comfort with early-stage startup reality", "qualificationsPreferred" : "Shipped developer API/platform product, Worked closely with sales/solutions teams, Led sales/solutions motion, Built/contributed AI agents, Built/contributed retrieval systems, Built/contributed search infrastructure, Public footprint in AI/developer-tools space", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "About Us At You.com, we are building the AI Search Infrastructure that powers modern AI systems. Our goal is to create the trusted knowledge layer that agents, applications, and enterprises rely on to retrieve real-time, accurate, and citation-backed information. Our platform combines proprietary vertical indexes with LLM-optimized retrieval systems to power AI agents, applications, and enterprise workflows. We are solving hard problems across search, large language models, and large-scale infrastructure to make AI systems more reliable, transparent, and useful. Our team includes engineers, researchers, product builders, and operators who care about solving meaningful problems and delivering real-world impact. Whether you are improving core infrastructure, shaping product experiences, or helping bring new AI capabilities to market, your work will help define how modern AI finds and uses knowledge. The role This is a hybrid product engineering and GTM role for someone who wants outsized impact at the intersection of all three. You'll own the direction of our API surface — shaping products like real-time monitoring, vertical feeds, and the next generation of agent-native retrieval primitives — while simultaneously sitting across the table from our most important customers to win, deploy, and expand high-value accounts. You'll be the technical voice customers trust, and the customer voice the engineering team trusts. The insights you bring back from the field will directly shape what we build next. This role demands high agency, deep customer obsession, and the rare ability to move fluidly between writing a technical product spec, debugging an integration on a customer call, and pitching a CTO on why our API should be core to their stack. What you'll do Own API product direction. Define the roadmap for our core search APIs and adjacent surfaces — monitoring, vertical feeds, evaluation tooling, and new primitives we haven't built yet. Decide what ships, when, and why. Lead solutions for strategic accounts. Partner directly with the founders and engineering leaders of our top customers and prospects. Architect their integration, unblock their teams, and turn pilots into long-term partnerships. Close the loop. Translate what you hear in customer conversations into concrete product bets. Write the specs, prioritize the roadmap, and make sure the highest-leverage learnings actually become shipped features. Be the technical face of the product. Run technical deep-dives, write the docs and reference implementations that matter most, and show up in the spaces where AI builders are deciding what to use. Set the technical bar. Work closely with engineering on API design, performance, and developer experience. Push back when something isn't good enough; ship when it is. Stay in the code. This is a hands-on role. You'll prototype new API primitives and ship production code into the core stack when the highest-leverage thing to do is just build it yourself. What you'll bring 5+ years of experience spanning engineering and product roles, with significant time spent on developer-facing or API products. You can still write production code and want to — this role expects it. Deep familiarity with the AI agent and LLM ecosystem — you understand how agents are being built, where retrieval fits in, and where the current tooling falls short. A track record of owning ambiguous, high-stakes problems end-to-end. You don't wait to be told what to do; you find the highest-leverage thing and go. Strong customer instincts. You enjoy customer calls, you're sharp at reading what's said and unsaid, and you can hold technical credibility with senior engineers and commercial credibility with executives. Excellent written and verbal communication. You can write a spec, a sales follow-up, and a postmortem with equal clarity. Comfort with the messy reality of an early-stage startup — shifting priorities, incomplete information, and the need to make calls without consensus. Bonus points You've shipped a developer API or platform product that real engineers depend on. You've worked closely with sales or solutions teams in a previous role, or led that motion yourself. You've built or contributed to AI agents, retrieval systems, or search infrastructure. You have a public footprint — open-source, writing, talks — in the AI or developer-tools space. Why this role Leverage. The decisions you make will compound across every customer we serve and every agent built on our APIs. Surface area. You'll touch product, engineering, GTM, and strategy. If you want a path toward a senior product or technical leadership role, this is rocket fuel. Learning & Collaboration. You'll work with world-class talent on search, infrastructure and AI problems. This team has a history on defining every part of the stack, you’ll never get bored! Timing. Agent infrastructure is one of the defining categories of this decade, and the next 18 months will determine who wins it. Compensation. Competitive base, meaningful equity, and the upside of a startup team building something foundational. Our salary bands are structured based on a combination of geographic tiers and internal leveling. Compensation is determined by multiple factors assessed during the interview process, with the final offer reflecting these considerations. Salary Band $200,000—$250,000 USD Company Perks: Hubs in San Francisco and New York City offering regular in-person gatherings and co-working sessions Flexible PTO with U. S. holidays observed and a week shutdown in December to rest and recharge* A competitive health insurance plan covers 100% of the policyholder and 75% for dependents* 12 weeks of paid parental leave in the US* 401k program, 3% match - vested immediately!* $500 work-from-home stipend to be used up to a year of your start date* $600 technology stipend to support a portion of our hybrid/remote team's cell phone and internet expenses* $1,200 per year Health & Wellness Allowance to support your personal goals* The chance to collaborate with a team at the forefront of AI research *Certain perks and benefits are limited to full-time employees only You.com participates in E-Verify. We will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s Form I-9 to confirm work authorization. (English/Spanish: E-Verify Participation/Right to Work) We are also an inclusive, equitable, and accessible workplace. Please let us know if you require accommodation for any portion of the recruitment and hiring process. Beware of recruiting scams: You.com will only contact you through official @You.com email addresses and will never ask for payment or sensitive personal information during the hiring process.", "summaryDescription" : "Senior AI Engineer, Product Engineering at You.com. Skills: AI Search Infrastructure, LLM, API Product Management. Own API product direction. Define roadmap for core search APIs", "postedDate" : "2026-06-15T23:22:13.298", "createdAt" : "2026-06-15T23:22:13.298", "lastUpdated" : "2026-06-16T10:37:22.892", "ingestTimestamp" : "2026-06-15T23:22:13.298", "mongoId" : "6a3051f3f292fd229cf09724", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 175000, "salaryAnnualMax" : 250000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Real-time retrieval", "LLM optimization", "AI Search Infrastructure", "LLM", "API Product Management", "Product direction", "Solutions architecture", "Technical product spec", "Customer integration", "API design", "Developer experience", "Roadmap planning", "AI agent ecosystem", "LLM ecosystem", "Retrieval systems", "Search infrastructure", "Agent infrastructure", "Vertical indexes", "Large-scale infrastructure" ], "skillCount" : 19, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3079aef292fd229c034403", "title" : "Retail Data & Consumer Insights Intern", "company" : "Umami", "industry" : "Work-Based Learning", "salary" : { "min" : 15.0, "max" : 15.0, "currency" : "USD", "frequency" : "per-hour-wage" }, "location" : "Bentonville, AR", "locations" : [ "Bentonville, AR" ], "timestamp" : "2026-06-16T12:03:59.337", "fingerprint" : "6e536fffe8e3ec6e34e36a6a3478d006e6cd30d3a0d3d1e5023943cea511c667", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/acds/f1b59e1c-6037-430d-8bcd-38f63c131057/apply", "externalId" : "f1b59e1c-6037-430d-8bcd-38f63c131057", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bentonville", "state" : "Arkansas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "36.3728608,-94.2087870" } ], "locationText" : "Bentonville, Arkansas, United States", "employmentType" : "INTERNSHIP", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "Clippr plugin", "professionalSkills" : [ "Consumer insights", "Product insights", "Data collection", "Data entry", "Data analysis", "Reporting", "Competitive benchmarking", "Assortment mapping", "Consumer sentiment analysis", "Innovation pipeline prioritization", "Brand health analysis", "Opportunity sizing", "Workflow optimization", "Process improvements", "Database maintenance", "Knowledge repositories" ], "hardSkillsList" : [ "Data visualization", "Reporting" ], "hardSkills" : [ { "name" : "Data visualization", "level" : "intermediate" }, { "name" : "Reporting", "level" : "intermediate" } ], "majorSkills" : "Retail data, Consumer insights, AI", "majorSkillsList" : [ "Retail data", "Consumer insights", "AI" ], "coreResponsibilities" : "Capture product data, Capture pricing data, Capture packaging data, Capture assortment data, Maintain accuracy, Maintain consistency, Identify anomalies, Identify gaps, Identify trends, Flag data entry issues, Use Clippr plugin, Scrape retail product information, Tag retail product information, Organize retail product information, Execute standardized workflows, Support category scans, Support competitive benchmarking, Support assortment mapping, Structure data for analytics, Structure data for reporting, Gather review-based consumer sentiment data, Decode consumer pain points, Decode unmet needs, Decode competitive strengths, Decode competitive weaknesses, Support creation of category snapshots, Support creation of opportunity maps, Support creation of concept inputs, Support preparation of reports, Analyze patterns across retailers, Analyze patterns across categories, Analyze patterns across consumer feedback, Contribute to innovation pipeline prioritization, Organize data inputs, Synthesize data inputs, Assist with ad hoc research, Support internal documentation, Support workflow optimization, Participate in team meetings, Contribute to process improvements, Maintain internal databases, Maintain knowledge repositories, Provide general operational support", "teamCollaboration" : "Innovation team; Insights team; Product team", "domainKnowledge" : "CPG innovation; AI; Retail data; Product development", "domainList" : [ "cpg-innovation", "ai", "retail-data", "product-development" ], "domainSpecificKnowledge" : [ "CPG innovation", "AI", "Retail data", "Product development" ], "toolProficiency" : [ "Clippr plugin", "Microsoft Excel", "Google Sheets", "Tableau", "Power BI", "Looker Studio" ], "communicationSkills" : "Written communication; Verbal communication", "documentationSkills" : "Internal documentation", "continuousLearning" : "Learning new technologies", "problemSolvingSkills" : "Identify anomalies; Identify gaps; Identify trends; Decode consumer pain points; Decode unmet needs; Decode competitive strengths; Decode competitive weaknesses", "specialRequirements" : "No future visa sponsorship", "qualificationsBasic" : "Attention to detail, Proficiency with Microsoft Excel, Proficiency with Google Sheets, Ability to identify patterns, Ability to identify trends, Ability to identify inconsistencies in data, Ability to work independently, Ability to manage multiple projects, Ability to meet deadlines, Current Arkansas state resident, Ability to pass a standard background check, Ability to work 40 hours a week, Ability to work full-time in the United States, Technical aptitude", "qualificationsPreferred" : "Familiarity with data visualization tools, Familiarity with reporting tools, Curious about CPG innovation, Excited to work at the intersection of AI, retail data, and product development, Interest in learning new technologies, Interest in growing IT career, Interest in starting IT career, Ability to communicate technical aptitude", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "## Description Apprenticely is working with our company partner, the Umami to add an Retail Data & Consumer Insights Intern to their team in Bentonville, Arkansas! Our Apprenticely Internship Program is a three-month program that places selected candidates with employers across Arkansas in IT positions to gain experience under the guidance of a professional mentor/IT support team. Internships are designed as an on-ramp to an IT career and can roll into full-time positions based on employer demand. About Umami: Umami is an AI-enabled, customer-driven Food & Beverage innovation platform built to analyze customer feedback and company advantages to generate strategic product insights for innovators within consumer-driven brands. We combine machine learning, consumer data, and brands’ unique advantages—from insight to innovation. FIELDBOOK, a studio operated by Alloy Partners, is dedicated to creating and accelerating advantaged “retail value chain” startups. We are launching Umami out of Fieldbook Studio—backed by the Walton Family Foundation and the Arkansas Development Finance Authority (ADFA). About the Role: The Intern will support Umami’s retail data collection and consumer insights workflows using the Clippr plugin and related internal tools. This role is ideal for someone who is detail‑oriented, curious about CPG innovation, and excited to work at the intersection of AI, retail data, and product development. ## Intern Responsibilities Capture product, pricing, packaging, and assortment data across assigned retailers and categories Maintain accuracy and consistency across large datasets Identify anomalies, gaps, or trends during data entry and flag them for review Use the Clippr plugin to scrape, tag, and organize retail product information Execute standardized workflows to support category scans, competitive benchmarking, and assortment mapping Ensure data is properly structured for downstream analytics and reporting Assist in gathering review-based consumer sentiment data aligned with Umami’s methodology (real reviews, not social media) Help decode consumer pain points, unmet needs, and competitive strengths/weaknesses Support the creation of category snapshots, opportunity maps, and early-stage concept inputs Support the preparation of internal and client-facing reports, including charts, summaries, and insights Help analyze patterns across retailers, categories, and consumer feedback Contribute to innovation pipeline prioritization work by organizing and synthesizing data inputs Collaborate with the Innovation, Insights, and Product teams as needed Assist with ad hoc research tasks related to brand health, innovation reports, and opportunity sizing Support internal documentation and workflow optimization Participate in team meetings and contribute to process improvements Help maintain internal databases and knowledge repositories Provide general operational support as the company scales its AI-powered product development platform ## Qualifications of an ideal candidate Strong attention to detail with the ability to maintain accuracy across large datasets. Proficiency with Microsoft Excel and/or Google Sheets. Familiarity with data visualization and reporting tools such as Tableau, Power BI, Looker Studio, or similar platforms. Excellent organizational and time management skills. Strong written and verbal communication skills. Ability to identify patterns, trends, and inconsistencies in data. Comfortable learning new software tools and technology platforms. Ability to work independently while managing multiple projects and deadlines. ## Additional Details Pay Range: $15/hr Schedule: 40-hour week: typically 8 a.m. - 5 p.m. Monday-Friday Length of Internship: 3 months with the potential to convert to a full-time opportunity based on employer demand Location: Bentonville, Arkansas ## Our Must Haves Current Arkansas state resident Ability to pass a standard background check Ability to work 40 hours a week, following the three-month internship Ability to work full-time in the United States without a current or future need for visa sponsorship High curiosity and interest in learning new technologies and growing or starting your IT career Technical aptitude exhibited through projects, experience, or online learning and the ability to communicate what you know ## Additional Information How does the interview process work? Apprenticely will conduct an initial phone interview and assessment. Apprenticely will send selected resumes to companies that match the candidate’s skills and interests. Our employer partners will decide who to interview and select the final candidates for the internship program. Meet the Apprenticely team and join our upcoming virtual webinars via zoom; dates and details are on our events page. Check out our YouTube page for past webinars and career tips! Learn more about us @ www.acds.co & LinkedIn, Facebook, Instagram & Twitter The Arkansas Center for Data Sciences dba Apprenticely will not discriminate against apprenticeship applicants or apprentices based on RACE, COLOR, RELIGION, NATIONAL ORIGIN, SEX (INCLUDING PREGNANCY AND GENDER IDENTITY), SEXUAL ORIENTATION, GENETIC INFORMATION, OR BECAUSE THEY ARE AN INDIVIDUAL WITH A DISABILITY OR A PERSON 40 YEARS OLD OR OLDER. Apprenticely will take affirmative action to provide equal opportunity in apprenticeship and will operate the apprenticeship program as required under Title 29 of the Code of Federal Regulations, part 30 SMS terms: Arkansas Center for Data Sciences (ACDS) DBA Apprenticely offers you the option to engage in SMS text conversations about your application for jobs and training programs. By participating, you also understand that message frequency may vary depending on the status of your job application, and that message and data rates may apply. Please consult your carrier for further information on applicable rates and fees. Carriers are not liable for delayed or undelivered messages. Reply STOP to cancel and HELP for help. View our Privacy & SMS Policy: https://apprenticely.org/privacy-policy/", "summaryDescription" : "Retail Data & Consumer Insights Intern at Umami. Skills: Retail data, Consumer insights, AI. Capture product data. Capture pricing data", "postedDate" : "2026-06-15T14:23:33.187", "createdAt" : "2026-06-15T14:23:33.187", "lastUpdated" : "2026-06-16T12:03:59.337", "ingestTimestamp" : "2026-06-16T03:26:12.618", "mongoId" : "6a3079aef292fd229c034403", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMax" : 15, "salaryBand" : "<30k", "hasSalary" : false, "allSkills" : [ "Data visualization", "Reporting", "Retail data", "Consumer insights", "AI", "Product insights", "Data collection", "Data entry", "Data analysis", "Competitive benchmarking", "Assortment mapping", "Consumer sentiment analysis", "Innovation pipeline prioritization", "Brand health analysis", "Opportunity sizing", "Workflow optimization", "Process improvements", "Database maintenance", "Knowledge repositories", "CPG innovation", "Product development", "Clippr plugin", "Microsoft Excel", "Google Sheets", "Tableau", "Power BI", "Looker Studio" ], "skillCount" : 27, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Food & Beverage", "llmIndustryConfidence" : 0.95 }, { "id" : "68c2e43bf8b1b0376634c92b", "title" : "Business Intelligence Engineer, P2 Science, Data, and Insights", "company" : "Amazon Development Centre Canada ULC", "industry" : "Business Intelligence, Business Intel Engineer, north america stores", "salary" : { "min" : 76400.0, "max" : 127600.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, CAN", "locations" : [ "Vancouver, British Columbia, CAN" ], "timestamp" : "2026-06-15T09:55:25.379", "fingerprint" : "58cefa08c8e6c631da3f1b5712d738e9918d8d4a111892f31a5b797fda68a7e6", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3071384/apply", "externalId" : "727f31ff-d576-4901-8950-4401fc137ada", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "SQL, Python, R, Redshift, NoSQL, Tableau, Quicksight, ETL, LLMs", "professionalSkills" : [ "Business intelligence", "Data modeling", "ETL pipelines", "Statistical analysis", "Data visualization", "Pricing strategy", "Promotions strategy", "Anomaly detection", "Business strategy", "Data infrastructure", "Data quality", "Data solutions" ], "hardSkillsList" : [ "Data analysis", "Data modeling", "ETL development", "Data visualization", "Statistical analysis", "Metric development", "SQL querying", "Python scripting", "Anomaly detection", "Reporting systems", "Dashboard creation", "Data quality implementation", "Data solution architecture" ], "softSkillsList" : [ "Curiosity", "Customer obsession", "Entrepreneurial spirit" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "ETL development", "level" : "intermediate" }, { "name" : "Data visualization", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Metric development", "level" : "intermediate" }, { "name" : "SQL querying", "level" : "intermediate" }, { "name" : "Python scripting", "level" : "intermediate" }, { "name" : "Anomaly detection", "level" : "intermediate" }, { "name" : "Reporting systems", "level" : "intermediate" }, { "name" : "Dashboard creation", "level" : "intermediate" }, { "name" : "Data quality implementation", "level" : "intermediate" }, { "name" : "Data solution architecture", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Curiosity" }, { "name" : "Customer obsession" }, { "name" : "Entrepreneurial spirit" } ], "majorSkills" : "Business intelligence, Data engineering, Analytics", "majorSkillsList" : [ "Business intelligence", "Data engineering", "Analytics" ], "coreResponsibilities" : "Spearhead business intelligence initiatives, Develop advanced analytical metrics, Develop advanced analytical models, Present compelling insights, Present recommendations to senior leadership, Harness LLMs, Generate business impacting insights, Lead data-driven discussions, Pioneer new methodologies, Design automated reporting systems, Create intuitive dashboards, Transform complex data, Innovate tools, Simplify processes, Enhance back-end data sources, Improve accuracy, Streamline operations, Implement data quality best practices, Implement modeling best practices, Architect scalable data solutions, Craft compelling narratives from data, Develop effective metrics, Collaborate across teams, Drive adoption of data-driven strategies, Champion a culture of innovation, Seek ways to improve, Seek ways to automate, Stay at forefront of BI trends, Bring developing technologies, Mentor colleagues, Elevate team capabilities", "teamCollaboration" : "Cross-functional teams; Product teams; Across teams", "domainKnowledge" : "Pricing; Promotions; Retail pricing; Customer behavior; Market dynamics", "domainList" : [ "pricing", "promotions", "retail-pricing", "customer-behavior", "market-dynamics" ], "domainSpecificKnowledge" : [ "Pricing", "Promotions", "Retail pricing", "Customer behavior", "Market dynamics" ], "toolProficiency" : [ "Tableau", "Quicksight", "Redshift", "Python" ], "communicationSkills" : "Presenting insights; Presenting recommendations; Crafting narratives", "continuousLearning" : "Learning new technologies; Stay at forefront of BI trends", "innovationCreativity" : "Innovate in fast-paced environment; Pioneer new methodologies; Innovate tools; Innovate processes; Culture of innovation", "problemSolvingSkills" : "Solving complex problems; Simplify complex problems", "outcomesObjectives" : "Drive pricing and promotions decisions; Shape business strategy; Drive customer satisfaction; Influence business growth; Enhance customer experience; Drive efficiency; Maximize impact; Improve accuracy; Streamline operations; Grow with the business; Influence key stakeholders; Shape future of pricing; Shape future of promotions; Drive adoption of strategies; Improve and automate; Elevate team capabilities; Impact customer experience; Impact business growth", "qualificationsBasic" : "3+ years analyzing data, Experience with Redshift, Experience with Oracle, Experience with NoSQL, Experience as BIE, Experience with Tableau, Experience with Quicksight, Experience with data modeling, Experience with warehousing, Experience building ETL, Experience with R, Experience with SAS, Experience with Matlab, Experience developing metrics, Experience presenting recommendations, Experience using SQL, Scripting experience (Python), Bachelors Degree", "qualificationsPreferred" : "Experience with EC2, Experience with DynamoDB, Experience with S3, Experience with Redshift, Experience in data mining, Experience with ETL, Experience using databases, Experience with large-scale datasets, Experience with complex datasets", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Shape How Amazon Serves Millions Through Pricing and Promotions Ready to transform how customers experience Amazon? Join our Pricing & Promotions Science, Data, and Insights team, where your analytical expertise will directly influence pricing and promotions decisions that impact millions of customers globally. Your Impact As a Business Intelligence Engineer, you'll be at the heart of Amazon's data-driven culture, building automated analytics tools that power intelligent pricing and promotions decisions. Your insights will shape strategy, drive customer satisfaction, and influence business growth across one of Amazon's most critical functions. What Makes You a Great Fit - You're a hands-on engineer who thrives on solving complex problems - You have an insatiable curiosity and love learning new technologies - You see opportunities where others see challenges - You build trust through delivery and customer obsession - You bring an entrepreneurial spirit to everything you do What You'll Create - Automated analytics systems that drive pricing and promotions decisions - Sophisticated anomaly detection tools - Data-driven insights that shape business strategy - Solutions that simplify complex problems - Tools that enhance customer experience Why This Role - Direct impact on Amazon's core business decisions - Opportunity to innovate in a fast-paced environment - Work with advanced analytics technologies - Shape the future of retail pricing and promotions - Join a team that values curiosity and creativity Transform data into decisions that matter. Join us in making Amazon the most customer-centric company through intelligent pricing solutions. Key job responsibilities Drive Strategic Insights - Spearhead business intelligence initiatives that directly impact Amazon's pricing and promotions strategy - Develop advanced analytical metrics and models to uncover hidden business opportunities - Present compelling insights and recommendations to senior leadership, influencing key decisions Innovate with Advanced Analytics - Harness the power of Large Language Models (LLMs) to generate business impacting insights - Lead data-driven discussions with Product teams to accelerate growth - Pioneer new methodologies in pricing and promotions analytics, setting industry standards Build Scalable Solutions - Design and implement automated reporting systems that drive efficiency - Create intuitive dashboards that transform complex data into clear, actionable insights - Continuously innovate and simplify tools and processes, maximizing impact Optimize Data Infrastructure - Enhance back-end data sources to improve accuracy and streamline operations - Implement best practices in data quality and modeling - Architect scalable data solutions that grow with the business Influence Through Communication - Craft compelling narratives from data, influencing key stakeholders - Develop effective metrics that shape the future of Amazon's pricing and promotions - Collaborate across teams to drive adoption of data-driven strategies Lead Continuous Improvement - Champion a culture of innovation, constantly seeking ways to improve and automate - Stay at the forefront of BI trends, bringing developing technologies to the team - Mentor colleagues in advanced analytics techniques, elevating team capabilities In this role, you'll be at the forefront of shaping how Amazon prices and promotes products globally. Your analytical expertise will directly impact customer experience and business growth, making you a key player in Amazon's mission to be Earth's most customer-centric company. About the team The Pricing and Promotions (P2) Science, Data and Insights team is at the forefront of Amazon's data revolution, orchestrating a sophisticated ecosystem with hundreds of PBs of data and thousands of active datasets that empower business leaders to create exceptional customer experiences through data-driven pricing and promotional strategies. Our team combines deep engineering expertise with business acumen to manage mission-critical data and insights that influence billions in revenue decisions, while pioneering innovative approaches that transform how Amazon understands customer behavior and market dynamics. Our strength comes from the diverse perspectives and backgrounds of our team members, who bring unique problem-solving approaches to these complex challenges. We're currently implementing an ambitious three-year transformation strategy that will fundamentally reshape how Amazon makes pricing and promotional decisions, focusing on intelligent automation and proactive insights that drive business outcomes. Beyond managing science, data, and insights, we're true strategic partners who translate complex information into actionable intelligence that shapes Amazon's direction across global marketplaces. If you're passionate about solving complex business problems at massive scale while working in a collaborative culture that values both analytical rigor and business impact, you'll find compelling opportunities to grow and make a meaningful difference on our team. Basic Qualifications: - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - Experience working as a BIE in a technology company - Experience with data visualization using Tableau, Quicksight, or similar tools - Experience with data modeling, warehousing and building ETL pipelines - Experience in Statistical Analysis packages such as R, SAS and Matlab - Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling - Bachelors Degree Preferred Qualifications: - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary for this position ranges from $76,400/year up to $127,600/year. Salary is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. Applicants should apply via our internal or external career site.", "summaryDescription" : "Business Intelligence Engineer, P2 Science, Data, and Insights at Amazon Development Centre Canada ULC. Skills: Business intelligence, Data engineering, Analytics. Spearhead business intelligence initiatives. Develop advanced analytical metrics", "postedDate" : "2026-06-13T15:15:17.936", "createdAt" : "2026-06-13T15:15:17.936", "lastUpdated" : "2026-06-15T09:55:25.379", "ingestTimestamp" : "2026-06-13T15:15:17.936", "mongoId" : "68c2e43bf8b1b0376634c92b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3071384/apply", "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Data analysis", "Data modeling", "ETL development", "Data visualization", "Statistical analysis", "Metric development", "SQL querying", "Python scripting", "Anomaly detection", "Reporting systems", "Dashboard creation", "Data quality implementation", "Data solution architecture", "Curiosity", "Customer obsession", "Entrepreneurial spirit", "Business intelligence", "Data engineering", "Analytics", "ETL pipelines", "Pricing strategy", "Promotions strategy", "Business strategy", "Data infrastructure", "Data quality", "Data solutions", "Pricing", "Promotions", "Retail pricing", "Customer behavior", "Market dynamics", "Tableau", "Quicksight", "Redshift", "Python" ], "skillCount" : 35, "jobCategory" : "other", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a3055f5f292fd229cf2360d", "title" : "Sr/Lead AI Backend Data Engineering - GenAI", "company" : "FICO", "salary" : { "min" : 140000.0, "max" : 140000.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "Work from Home, United States", "locations" : [ "Work from Home, United States", "United States of America" ], "timestamp" : "2026-06-16T15:06:50.768", "fingerprint" : "2991cf46031b9a1732134d3ad307d132073705171cf29a3088a41e8021951fc7", "source" : "workday", "language" : "en", "applyUrl" : "https://fico.wd1.myworkdayjobs.com/External/job/Work-from-Home-United-States/Sr-Lead-AI-Backend-Data-Engineering---GenAI_31937", "externalId" : "31937", "industryFunction" : { }, "locationPoint" : "47.27482,-122.76375", "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "**FICO (NYSE: FICO)** is a leading global analytics software company, helping businesses in 100+ countries make better decisions. Join our world-class team today and fulfill your career potential! **The Opportunity** As a Senior or Lead Backend Engineer on our Applied AI team, you will be at the forefront of integrating robust data engineering with next-generation AI capabilities. You will design, build, and maintain scalable backend systems and data pipelines that power critical functions across our platform — from fraud investigation and decision automation to process optimization. In this role, you will champion high data quality, system reliability, and stringent governance across all AI-driven initiatives, making a lasting impact on FICO's platform. This is an opportunity to collaborate with a high-caliber team and drive meaningful innovation through your deep expertise in backend engineering and applied AI. **What You 'll Contribute** * Design and deploy scalable backend systems and data pipelines that seamlessly integrate applied AI capabilities into FICO's analytics and decision management platform. * Build high-quality solutions for data ingestion, transformation, and storage, ensuring reliable, high-throughput data flow for real-time analytics. * Design and implement LLM-powered solutions for decision automation, fraud investigation, and process automation within FICO's platform. * Develop sophisticated prompting strategies and Retrieval-Augmented Generation (RAG) architectures tailored to high-stakes, mission-critical applications. * Partner with data scientists, ML engineers, and product teams to develop microservices and APIs that enable intelligent, data-driven decision-making. * Optimize distributed architectures and implement real-time processing frameworks to support high-volume, low-latency workloads. * Implement advanced monitoring, testing, and performance optimization techniques to ensure system reliability, security, and scalability. * Define and evolve architectural patterns that support FICO's analytics and decisioning solutions at scale. * Lead and mentor engineering team members, promoting best practices in software development, data engineering, AI integration, and systems design. **What We 're Seeking** * In-depth experience in backend or data engineering, with a demonstrated track record of delivering complex, large-scale production systems. * Strong coding skills in Python, Go, Java, or equivalent languages, with a commitment to clean, maintainable, and well-tested code. * Hands-on experience with big data frameworks (e.g., Apache Spark, Kafka, Hadoop) and a strong understanding of both relational and NoSQL databases. * Experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools such as Docker and Kubernetes. * Proven ability to design, build, and maintain scalable, production-grade backend systems with a focus on reliability and performance. * Solid experience with testing frameworks (including A/B testing), performance optimization, and production monitoring/observability practices. * Demonstrated experience integrating AI/ML solutions into production systems, including working with Large Language Models (LLMs) and related techniques. * Experience with Retrieval-Augmented Generation (RAG) architectures and familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector) is strongly preferred. * Strong problem-solving and communication skills, with the ability to mentor engineers, influence technical direction, and collaborate effectively across disciplines. * Bachelor's or Master's degree in Computer Science, Engineering, or a related field. An advanced degree is a plus but not required. **Our Offer to You** * An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others. * The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences. * Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so. * An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie. * The targeted base pay range for this role is: $140,000 to $220,000 with this range reflecting differences in candidate knowledge, skills and experience. #LI-LS1 #LI-remote **Why Make a Move to FICO?** At FICO, you can develop your career with a leading organization in one of the fastest-growing fields in technology today – Big Data analytics. You’ll play a part in our commitment to help businesses use data to improve every choice they make, using advances in artificial intelligence, machine learning, optimization, and much more. FICO makes a real difference in the way businesses operate worldwide: • Credit Scoring — FICO® Scores are used by 90 of the top 100 US lenders. • Fraud Detection and Security — 4 billion payment cards globally are protected by FICO fraud systems. • Lending — 3/4 of US mortgages are approved using the FICO Score. Global trends toward digital transformation have created tremendous demand for FICO’s solutions, placing us among the world’s top 100 software companies by revenue. We help many of the world’s largest banks, insurers, retailers, telecommunications providers and other firms reach a new level of success. Our success is dependent on really talented people – just like you – who thrive on the collaboration and innovation that’s nurtured by a diverse and inclusive environment. We’ll provide the support you need, while ensuring you have the freedom to develop your skills and grow your career. Join FICO and help change the way business thinks! Learn more about how you can fulfil your potential at [www.fico.com/Careers](http://www.fico.com/Careers) FICO promotes a culture of inclusion and seeks to attract a diverse set of candidates for each job opportunity. We are an equal employment opportunity employer and we’re proud to offer employment and advancement opportunities to all candidates without regard to race, color, ancestry, religion, sex, national origin, pregnancy, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Research has shown that women and candidates from underrepresented communities may not apply for an opportunity if they don’t meet all stated qualifications. While our qualifications are clearly related to role success, each candidate’s profile is unique and strengths in certain skill and/or experience areas can be equally effective. If you believe you have many, but not necessarily all, of the stated qualifications we encourage you to apply. Information submitted with your application is subject to the FICO Privacy policy at [https://www.fico.com/en/privacy-policy](https://www.fico.com/en/privacy-policy)", "summaryDescription" : "Sr/Lead AI Backend Data Engineering - GenAI at FICO", "postedDate" : "2026-06-16T03:46:56.127", "createdAt" : "2026-06-16T03:46:56.104", "lastUpdated" : "2026-06-16T15:06:50.768", "ingestTimestamp" : "2026-06-16T03:46:56.104", "mongoId" : "6a3055f5f292fd229cf2360d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://fico.wd1.myworkdayjobs.com/External/job/Work-from-Home-United-States/Sr-Lead-AI-Backend-Data-Engineering---GenAI_31937", "salaryAnnualMin" : 140000, "salaryAnnualMax" : 140000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2cfbd074d8ee00a0aa5831", "title" : "Senior AI Data Engineer", "company" : "Cortica", "industry" : "Healthcare", "salary" : { "min" : 160000.0, "max" : 200000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "San Diego, California, United States", "locations" : [ "San Diego", "California", "United States" ], "timestamp" : "2026-06-15T21:42:45.289", "fingerprint" : "46bd2ff40e69e2e1ed36e7e3055ccd8f3bf789381e2c8a078249c72ea7e558b6", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/allcareers/jobs/8590529002", "externalId" : "8590529002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Diego", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "32.7174202,-117.1627720" } ], "locationText" : "San Diego, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL, AWS, Azure", "professionalSkills" : [ "System design", "Application development" ], "hardSkillsList" : [ "Data pipelines", "Data models" ], "hardSkills" : [ { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Data models", "level" : "intermediate" } ], "majorSkills" : "AI Data Engineering, Data pipelines, Data models", "majorSkillsList" : [ "AI Data Engineering", "Data pipelines", "Data models" ], "coreResponsibilities" : "Own projects end-to-end, Design data pipelines, Build data pipelines, Develop data models, Evolve data models, Use AI-assisted development, Build internal tools, Build dashboards, Ensure data security, Ensure compliance", "teamCollaboration" : "Data science teams; Finance teams; Clinical operations teams; Across teams", "domainKnowledge" : "Neurodevelopmental differences; Healthcare", "domainList" : [ "neurodevelopmental-differences", "healthcare" ], "domainSpecificKnowledge" : [ "Neurodevelopmental differences", "Healthcare" ], "continuousLearning" : "Tuition reimbursements; Continuing education", "qualificationsBasic" : "5+ years of experience designing and building production data pipelines, 2+ years of experience working with AI-first development workflows, Fluent in Python and SQL at an advanced level, 4+ years of experience with AWS and/or Azure big data services, 2+ years of experience with orchestration frameworks, Possess application development literacy", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Cortica is looking for a Senior AI Data Engineer to join its growing team! Cortica is a rapidly growing healthcare company pioneering the most effective treatment methods for children with neurodevelopmental differences. Our mission is to design and deliver life-changing care – one child, one family, one community at a time. Ultimately, we envision a world that cultivates the full potential of every child. At Cortica, every team member is instrumental in helping us achieve our mission! Our culture and values guide how we work and treat one another. Cortica celebrates diversity and fosters an inclusive environment, seeking ideas and opinions from everyone on the team. We safeguard equal rights and respect for all individuals, regardless of race, color, religion, sex, national origin, age, disability, creed, genetic information, sexual orientation, gender identity or expression, ancestry, veteran status or other applicable, legally protected characteristics. All Cortica employment decisions are made based on an individual’s qualifications and ability to successfully perform the job responsibilities. What will you do? The Senior AI Data Engineer will serve as both architect and builder of our data ecosystem. You’ll work closely with the data science, finance, and clinical operations teams to design intelligent, automated data solutions that power care decisions, financial planning, and operational efficiency. Own projects end-to-end: From stakeholder requirements through production deployment Design and build data pipelines that are reliable, scalable, and maintainable Develop and evolve data models that support clinical, financial, and operational reporting Use AI-assisted development as a core part of your daily workflow Build lightweight internal tools and dashboards where pipelines alone aren't enough Ensure data security and compliance across all work Collaborate across teams and document decisions so others can build on your work We’d love to hear from you if: You have 5+ years of experience designing and building production data pipelines. You bring 2+ years of experience working with AI-first development workflows. You're fluent in Python and SQL at an advanced level You bring 4+ years of experience with the following AWS and/or Azure big data services You have 2+ years of experience with orchestration frameworks You possess application development literacy to lightweight web tooling to complement data products. Your Compensation & Benefits Cortica cares deeply about the well-being of each member of our team, and we have created a passionate, caring, and growth-minded culture that helps teammates thrive! As a Cortica teammate, we’ll support your well-being through medical, dental, and vision insurance, a 401(k) plan with company matching and rapid vesting, paid holidays and wellness days, life insurance, disability insurance options, tuition reimbursements for professional development and continuing education, and referral bonuses. We value you and the experience you bring to your role, and are proud to provide you with a compensation and benefits package designed to enhance all aspectsof your life. The base pay range for this opening is $160,000 to $200,000. According to your skill level, relevant experience, education level, and location, you will receive compensation that fits appropriately within the range. EOE. This posting is not meant to be an exhaustive list of the role and its duties. #LI-NF1 #LI-Onsite", "summaryDescription" : "Senior AI Data Engineer at Cortica. Skills: AI Data Engineering, Data pipelines, Data models. Own projects end-to-end. Design data pipelines", "postedDate" : "2026-06-14T20:18:29.446", "createdAt" : "2026-06-14T20:18:29.446", "lastUpdated" : "2026-06-15T21:42:45.289", "ingestTimestamp" : "2026-06-14T20:18:29.446", "mongoId" : "6a2cfbd074d8ee00a0aa5831", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 160000, "salaryAnnualMax" : 200000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipelines", "Data models", "AI Data Engineering", "System design", "Application development", "Neurodevelopmental differences", "Healthcare" ], "skillCount" : 7, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a305649f292fd229cf26d26", "title" : "Sr. Prototyping Architect, AWS Prototyping and AI Customer Engineering (PACE)", "company" : "Amazon Web Services Canada, Inc.", "industry" : "Solutions Architect, Solution Architect, Cloud Computing", "salary" : { "min" : 146000.0, "max" : 211600.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Toronto, Ontario, CAN", "locations" : [ "Toronto, Ontario, CAN" ], "timestamp" : "2026-06-16T08:43:09.321", "fingerprint" : "1794540c9b1db75187b89301fc769760cb9ccbfb458d517a5ceaaaf168e58274", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10449045/apply", "externalId" : "decadc61-ab2e-4f68-a88c-042e2692b2fe", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.6534817,-79.3839347" } ], "locationText" : "Toronto, Ontario, Canada", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Java, C++, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Cloud Computing, AWS, Azure, GCP, Distributed Systems, Data Structures, Algorithms, Software Development, API Development, Databases, SQL, NoSQL, Containerization, Docker, Kubernetes, MLOps", "professionalSkills" : [ "System Design", "Problem Solving", "Analytical Skills", "Technical Leadership", "Project Management" ], "hardSkillsList" : [ "Software Engineering", "Machine Learning Engineering", "AI Development", "Cloud Architecture", "Data Engineering", "Algorithm Design", "System Optimization" ], "hardSkills" : [ { "name" : "Software Engineering", "level" : "intermediate" }, { "name" : "Machine Learning Engineering", "level" : "intermediate" }, { "name" : "AI Development", "level" : "intermediate" }, { "name" : "Cloud Architecture", "level" : "intermediate" }, { "name" : "Data Engineering", "level" : "intermediate" }, { "name" : "Algorithm Design", "level" : "intermediate" }, { "name" : "System Optimization", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, AI Development, Cloud Computing, Distributed Systems", "majorSkillsList" : [ "Machine Learning", "AI Development", "Cloud Computing", "Distributed Systems" ], "coreResponsibilities" : "Design and implement scalable AI/ML solutions, Develop and deploy machine learning models, Build and maintain data pipelines, Collaborate with cross-functional teams, Optimize model performance and efficiency, Stay up-to-date with AI/ML advancements, Contribute to architectural decisions, Mentor junior engineers", "teamCollaboration" : "Cross-functional teams; Engineering teams; Product managers; Research scientists", "projectManagementSkills" : [ "Agile methodologies", "Scrum", "Project planning" ], "domainKnowledge" : "Artificial Intelligence; Machine Learning; Deep Learning; Cloud-native architecture; Large-scale systems", "domainList" : [ "artificial-intelligence", "machine-learning", "deep-learning", "cloud-native-architecture", "large-scale-systems" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Machine Learning", "Deep Learning", "Cloud-native architecture", "Large-scale systems" ], "toolProficiency" : [ "TensorFlow", "PyTorch", "Scikit-learn", "Spark", "Hadoop", "Git", "JIRA" ], "communicationSkills" : "Technical presentations; Documentation", "documentationSkills" : "Technical documentation; Architecture diagrams", "continuousLearning" : "Professional development; Attending conferences", "innovationCreativity" : "Research and development; Prototyping", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; Analytical thinking", "qualificationsBasic" : "Bachelor's degree or equivalent practical experience, 5+ years of experience in software development, Experience with cloud computing services (AWS, Azure, GCP), Experience with large-scale distributed systems, Experience with machine learning or AI development", "qualificationsPreferred" : "Master's degree or PhD in Computer Science or related field, Experience with MLOps practices, Experience with containerization technologies (Docker, Kubernetes), Experience with data processing and analytics tools, Publications in relevant AI/ML conferences or journals", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Build the future of AI innovation alongside AWS's most forward-thinking customers. The AWS Prototyping and AI Customer Engineering (PACE) team transforms ambitious ideas into working Generative AI and Agentic AI prototypes in days and weeks - not months - and we need world-class builders who can turn customer visions into reality. If you're passionate about full-stack development, love experimenting with cutting-edge AI technologies, and thrive on shipping prototypes that demonstrate what's possible with large language models, autonomous agents, and multi-agent systems, this is your opportunity to make history. In this role, you'll work hands-on with customers to architect and build production-ready AI prototypes using the latest Generative AI technologies - from prompt engineering and RAG architectures to function calling, autonomous agents, and complex multi-agent orchestration. You'll leverage AI-driven development tools to write code faster, exploring agentic workflows where AI systems can reason, plan, use tools, and collaborate to solve complex problems. You'll be a full-stack developer comfortable with multiple languages and frameworks, combining modern application patterns with AWS AI services to rapidly deliver solutions that showcase the transformative potential of Generative AI and Agentic AI. This isn't traditional consulting - you'll be writing code, making architectural decisions about agent behaviors and LLM integrations, and creating breakthrough experiences that influence how organizations globally approach AI adoption. Position requires travel - generally 25% Key job responsibilities - Architect and build working Generative AI and Agentic AI prototypes directly with customers using AWS AI services (Bedrock, SageMaker, Q Developer) and cloud-native architectures, including autonomous agents, multi-agent systems, RAG architectures, and LLM-powered applications that demonstrate production-ready solutions - Leverage AI-driven development tools (Cursor, Kiro, Q Developer, Cline, Windsurf) to accelerate prototype development, implementing patterns like prompt engineering, function calling, agent orchestration, and tool use - Serve as a trusted technical advisor to customers on LLM selection, agent design patterns, agentic architectures, and AI adoption strategies, guiding them through complex technical decisions and trade-offs - Collaborate with Technical Program Managers and Design Technologists to deliver customer engagements on time, while partnering with AWS service teams to provide feedback and influence AI product roadmaps - Create and share reusable patterns and thought leadership through agent frameworks, code libraries, technical content, whitepapers, blogs, and conference presentations that accelerate Generative AI and Agentic AI adoption across the AWS customer base A day in the life Your morning starts with team standup where you and fellow Prototyping Architects align with your Technical Program Manager on customer momentum, breakthrough patterns, and hard problems at agentic AI's edge. Then into deep coding work building transformative agentic solutions, orchestrating multi-agent patterns integrated with AWS AI services. You make architectural decisions that drive measurable business outcomes: faster resolution, smarter recommendations, autonomous scaling. Mid-morning brings a strategic conversation with customer leadership on how agentic architectures power their business. Afternoon: architecting a retail shopping assistant with specialized agents, collaborating with Design Technologists. You document edge cases and patterns that become blueprints for future engagements. As day closes, you're context-switching between production code, architectural decisions, and translating innovation into strategic language for leadership. You're building solutions that illuminate the path for how enterprises adopt transformative AI. About the team The PACE team accelerates innovation for AWS customers, setting the direction for enterprise adoption. We're builders: Design Technologists, Technical Program Managers, and Prototyping Architects building solutions with world-class engineers using emerging technologies. We operate at technology's bleeding edge, embracing high-judgment experimentation as a catalyst for breakthrough innovation. We own decisions, partner with forward-thinking customers across industries, and move at unprecedented speed, delivering functional prototypes in weeks and scaling learnings across enterprises. Our work shapes how industries adopt transformative technology. We engage with customer executives, collaborate on novel problems, and drive impact globally. Basic Qualifications: - Knowledge of cloud architecture - 7+ years of design, implementation, or consulting in applications and infrastructures experience Preferred Qualifications: - Knowledge of software development tools and methodologies - AWS Certifications (Solutions Architect, Developer, or Machine Learning) or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status. CAN, ON, Toronto - 146,000.00 - 211,600.00 CAD annually", "summaryDescription" : "Sr. Prototyping Architect, AWS Prototyping and AI Customer Engineering (PACE) at Amazon Web Services Canada, Inc.. Skills: Machine Learning, AI Development, Cloud Computing, Distributed Systems. Design and implement scalable AI/ML solutions. Develop and deploy machine learning models", "postedDate" : "2026-06-15T00:00:00.000", "createdAt" : "2026-06-15T22:01:33.319", "lastUpdated" : "2026-06-16T08:43:09.321", "ingestTimestamp" : "2026-06-15T22:01:33.319", "mongoId" : "6a305649f292fd229cf26d26", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10449045/apply", "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Software Engineering", "Machine Learning Engineering", "AI Development", "Cloud Architecture", "Data Engineering", "Algorithm Design", "System Optimization", "Machine Learning", "Cloud Computing", "Distributed Systems", "System Design", "Problem Solving", "Analytical Skills", "Technical Leadership", "Project Management", "Agile methodologies", "Scrum", "Project planning", "Artificial Intelligence", "Deep Learning", "Cloud-native architecture", "Large-scale systems", "TensorFlow", "PyTorch", "Scikit-learn", "Spark", "Hadoop", "Git", "JIRA" ], "skillCount" : 29, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.97 }, { "id" : "6a305591f292fd229cf2033c", "title" : "AI Engineering Lead", "company" : "Planet", "salary" : { "min" : 70000.0, "max" : 110000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for AI Engineering Lead in Portugal, adjusted for Lead seniority and the Technology industry." }, "location" : "Portugal", "locations" : [ "Portugal" ], "timestamp" : "2026-06-16T11:48:37.456", "fingerprint" : "82499f3d6841d48e7d9d10804097ca6b027f3851f205816a4c7612cad7a141e7", "source" : "workday", "language" : "en", "applyUrl" : "https://planet.wd3.myworkdayjobs.com/Planet/job/Porto---Portugal/C--Software-Engineer_JR11259", "externalId" : "JR11259", "industryFunction" : { }, "locationPoint" : "39.3999,-8.2245", "structuredLocations" : [ { "country" : "Portugal", "continent" : "eu", "workMode" : "hybrid" } ], "locationText" : "Portugal", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "**About Planet** Planet is a global provider of integrated technology and payments solutions for retail and hospitality customers. We create great experiences for the millions of people who use our payments, software, and tax-free solutions every minute of every day. Planet empowers its customers to deliver great customer experiences by combining payments and software in ways that drive greater loyalty, increase revenue and save time. Founded over 35 years ago and with our headquarters in London, today we have more than 2,500 employees located across six continents serving our customers in more than 120 markets. **Role Overview** We are looking for a Senior Engineering & AI Tech Lead to provide hands‑on technical leadership for our on‑premise hospitality products, while systematically infusing AI into both the product roadmap and the day‑to‑day ways of working of the engineering team. The successful candidate will be equally comfortable owning complex C# / C++ systems, modernising legacy platforms, and pragmatically applying AI (LLMs, ML, automation) where it creates real customer or operational value — not experimentation for experimentation’s sake. This is a hands‑on role: you will design, code, review, coach, and lead by example while steadily raising the technical and delivery bar of the team. **What you will do** ### ### Technical & Product Leadership * Act as the technical authority for the on‑prem product suite, spanning legacy and modern components * Drive architecture, design decisions, and technical standards across C# and C++ codebases * Own the technical execution of the product roadmap, ensuring delivery predictability, quality, and sustainability * Partner closely with Product leadership to translate business goals into executable technical plans * Identify and reduce systemic technical debt and operational risk ### ### AI Enablement & Adoption * Identify high‑leverage AI opportunities across the product: automation, supportability, configuration, data quality, compliance, and operational efficiency * Lead the pragmatic adoption of AI / LLM‑based capabilities in production environments * Define standards for AI quality, testing, observability, security, and responsible use * Introduce AI‑assisted ways of working for the engineering team (e.g. development productivity, testing, diagnostics, documentation) * Ensure AI is embedded into normal delivery workflows, not treated as a standalone initiative ### ### Delivery Ownership * Take end‑to‑end accountability for delivery outcomes, including prioritisation, execution, and risk management * Establish and track engineering KPIs (predictability, quality, operational health) * Ensure systems meet legal, fiscal, security, and regulatory requirements relevant to on‑prem hospitality software ### ### Team Leadership & Enablement * Serve as a engineering team lead for the team as assigned * Lead through influence, coaching, and example rather than hierarchy * Mentor engineers; raise technical judgment and ownership across the team for AI * Shape common engineering practices: code reviews, testing strategies, CI/CD, documentation, incident handling * Gradually evolve team maturity, structure, and accountability as needed ### ### Ways of Working & Operational Excellence * Drive continuous improvement in engineering practices, tooling, and workflows * Introduce clearer technical decision‑making, ownership boundaries, and escalation paths * Improve collaboration across Product, Support, Operations, and Compliance **Who you are** ### ### Technical background * Strong professional experience in C# and C++ within complex commercial software products * Deep understanding of software architecture, distributed systems, and long‑lived codebases * Proven hands‑on experience delivering AI/ML or LLM‑based features into production * Comfortable modernising legacy systems while maintaining reliability for existing customers ### ### Leadership & mindset * Experienced technical leader who can run a team without relying on title or hierarchy * Pragmatic, outcome‑oriented, and commercially aware * Strong coach and mentor; raises the bar for others through clarity and example * Confident making—and standing behind—technical decisions ### ### Delivery & communication * Track record of delivering complex software predictably and safely * Able to communicate clearly with engineers, product managers, and senior stakeholders * Fluent English **Why Planet:** Planet is an equal opportunity employer where diversity is valued, and all employment is decided based on qualifications, merit, and business need. Come and grow your career in the most exciting, fast paced technology market, with a business that delivers feel-good connected commerce. **We would love to hear from you – Apply now**. At Planet, we embrace a hybrid work model, with three days a week in the office. Reasonable accommodations may be made in order to allow for an individual to perform the essential functions of this role successfully.", "summaryDescription" : "AI Engineering Lead at Planet", "postedDate" : "2026-06-16T03:46:32.751", "createdAt" : "2026-06-16T03:46:32.747", "lastUpdated" : "2026-06-16T11:48:37.456", "ingestTimestamp" : "2026-06-16T03:46:32.747", "mongoId" : "6a305591f292fd229cf2033c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://planet.wd3.myworkdayjobs.com/Planet/job/Porto---Portugal/C--Software-Engineer_JR11259", "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a30511af292fd229cefa48c", "title" : "Senior Product Manager, Customer Insights", "industry" : "Product", "salary" : { "min" : 75000.0, "max" : 110000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Product Manager in the Technology industry in Bulgaria, adjusted for seniority and remote work." }, "location" : "Canada", "locations" : [ "Canada" ], "timestamp" : "2026-06-16T13:03:47.596", "fingerprint" : "0d7b98f3cf4ba4103012106b5097798c477c356e660b0ff25a3656601e1f0034", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/1a27ef19-4c6f-48ca-86a3-ba515ee8f7ce/apply", "externalId" : "1a27ef19-4c6f-48ca-86a3-ba515ee8f7ce", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 4, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "professionalSkills" : [ "Product strategy", "Roadmap development", "Data modeling", "Reporting frameworks", "AI technologies", "Conversational analytics", "Proactive recommendations", "Intelligent workflows", "Data pipelines", "Aggregation strategies", "Data quality", "Scalability considerations", "Product-market fit", "Cross-functional leadership" ], "hardSkillsList" : [ "Analytics", "Reporting", "Business intelligence", "Data products", "Data models", "Instrumentation strategies", "Key metrics", "Reporting frameworks", "Data pipelines", "Aggregation strategies", "Data quality", "Scalability", "AI technologies", "Conversational analytics", "Proactive recommendations", "Intelligent workflows", "Audit capabilities", "Governance capabilities" ], "hardSkills" : [ { "name" : "Analytics", "level" : "intermediate" }, { "name" : "Reporting", "level" : "intermediate" }, { "name" : "Business intelligence", "level" : "intermediate" }, { "name" : "Data products", "level" : "intermediate" }, { "name" : "Data models", "level" : "intermediate" }, { "name" : "Instrumentation strategies", "level" : "intermediate" }, { "name" : "Key metrics", "level" : "intermediate" }, { "name" : "Reporting frameworks", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Aggregation strategies", "level" : "intermediate" }, { "name" : "Data quality", "level" : "intermediate" }, { "name" : "Scalability", "level" : "intermediate" }, { "name" : "AI technologies", "level" : "intermediate" }, { "name" : "Conversational analytics", "level" : "intermediate" }, { "name" : "Proactive recommendations", "level" : "intermediate" }, { "name" : "Intelligent workflows", "level" : "intermediate" }, { "name" : "Audit capabilities", "level" : "intermediate" }, { "name" : "Governance capabilities", "level" : "intermediate" } ], "majorSkills" : "Product strategy, Roadmap development, Analytics, Reporting, Data products, AI-powered insights", "majorSkillsList" : [ "Product strategy", "Roadmap development", "Analytics", "Reporting", "Data products", "AI-powered insights" ], "coreResponsibilities" : "Define product strategy, Execute product strategy, Define product roadmap, Execute product roadmap, Define product vision, Ensure alignment business objectives, Ensure alignment customer needs, Own end-to-end development analytics, Own end-to-end development reporting, Develop foundational data models, Develop customer-facing dashboards, Develop customer-facing reports, Develop audit logs, Develop APIs, Partner with engineering teams, Partner with data teams, Establish scalable data foundations, Establish meaningful usage metrics, Establish reporting frameworks, Support customer growth, Support customer retention, Lead evolution enterprise-grade audit, Lead evolution governance capabilities, Ensure usability audit capabilities, Ensure scalability audit capabilities, Ensure compliance readiness audit, Drive development AI-powered insights, Develop conversational analytics, Develop proactive recommendations, Develop intelligent workflows, Collaborate with Sales teams, Collaborate with Customer Success teams, Transform product data, Create compelling customer value narratives, Support renewals, Support account expansion, Engage directly with enterprise administrators, Engage directly with IT leaders, Engage directly with security stakeholders, Validate priorities, Ensure product-market fit, Work cross-functionally with adjacent teams, Create seamless experiences administration, Create seamless experiences identity management, Create seamless experiences security, Create seamless experiences governance, Translate complex business challenges, Translate ambiguous business challenges, Create intuitive product solutions, Create actionable product solutions", "teamCollaboration" : "Cross-functional teams; Engineering teams; Data teams; Sales teams; Customer Success teams; Adjacent product teams; Enterprise administrators; IT leaders; Security stakeholders", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Customer Insights; Data products; Analytics; Reporting; Business intelligence; Data models; Data pipelines; AI-native analytics; Insight-driven experiences; Enterprise administration; Governance; Identity management; Security; Compliance; Audit", "domainList" : [ "customer-insights", "data-products", "analytics", "reporting", "business-intelligence", "data-models", "data-pipelines", "ai-native-analytics", "insight-driven-experiences", "enterprise-administration", "governance", "identity-management", "security", "compliance", "audit" ], "domainSpecificKnowledge" : [ "Customer Insights", "Data products", "Analytics", "Reporting", "Business intelligence", "Data models", "Data pipelines", "AI-native analytics", "Insight-driven experiences", "Enterprise administration", "Governance", "Identity management", "Security", "Compliance", "Audit" ], "communicationSkills" : "Stakeholder management; Cross-functional leadership", "innovationCreativity" : "AI-powered insights experiences", "problemSolvingSkills" : "Analytical thinking; Problem-solving abilities; Translate complex challenges; Create actionable solutions", "outcomesObjectives" : "Support customer growth; Support customer retention; Support renewals; Support account expansion; Ensure product-market fit; Deliver measurable outcomes", "qualificationsBasic" : "4+ years product management experience, 2+ years analytics experience, 2+ years reporting experience, 2+ years business intelligence experience, 2+ years data-driven products experience, Define data models experience, Define instrumentation strategies experience, Define key metrics experience, Define reporting frameworks experience, Collaborate with engineering teams, Collaborate with data teams, Understand AI technologies, Convert complex business problems, Deliver measurable outcomes, Partner with customer-facing teams, Support customer success initiatives, Support customer retention initiatives, Support revenue growth initiatives, Analytical thinking, Problem-solving abilities, Comfort in evolving environments, Comfort in ambiguous environments", "qualificationsPreferred" : "Experience building enterprise administration products, Experience building governance products, Experience building identity and access management products, Experience building security products, Experience building compliance products, Experience building audit-related products, Background in business intelligence platforms, Background in analytics tools, Background in data-centric software products, Experience designing customer-facing APIs, Experience delivering customer-facing APIs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Define and execute the product strategy, roadmap, and vision for the Customer Insights domain, ensuring alignment between business objectives and customer needs. Own the end-to-end development of analytics and reporting capabilities, from foundational data models to customer-facing dashboards, reports, audit logs, and APIs. Partner with engineering and data teams to establish scalable data foundations, meaningful usage metrics, and reporting frameworks that support customer growth and retention. Lead the evolution of enterprise-grade audit and governance capabilities, ensuring usability, scalability, and compliance readiness. Drive the development of AI-powered insights experiences, including conversational analytics, proactive recommendations, and intelligent workflows. Collaborate with Sales and Customer Success teams to transform product data into compelling customer value narratives that support renewals and account expansion. Engage directly with enterprise administrators, IT leaders, and security stakeholders to validate priorities and ensure product-market fit. Work cross-functionally with adjacent product teams to create seamless experiences across administration, identity management, security, and governance domains. Translate complex and ambiguous business challenges into intuitive, actionable product solutions. Requirements 4+ years of product management experience, including at least 2 years focused on analytics, reporting, business intelligence, or data-driven products. Strong expertise in data products, with hands-on experience defining data models, instrumentation strategies, key metrics, and reporting frameworks. Ability to collaborate effectively with engineering and data teams on technical topics such as data pipelines, aggregation strategies, data quality, and scalability considerations. Demonstrated understanding of AI technologies and a strong perspective on the future of AI-native analytics and insight-driven experiences. Proven track record of converting complex business problems into successful product solutions that deliver measurable outcomes. Experience partnering with customer-facing teams to support customer success, retention, and revenue growth initiatives. Excellent communication, stakeholder management, and cross-functional leadership skills. Strong analytical thinking, problem-solving abilities, and comfort working in evolving and ambiguous environments. Preferred Qualifications Experience building enterprise administration, governance, identity and access management, security, compliance, or audit-related products. Background in business intelligence platforms, analytics tools, or data-centric software products. Experience designing and delivering customer-facing APIs for analytics, reporting, or data access use cases. Benefits Competitive salary package with a target compensation range of $160,000–$215,000 CAD equivalent, based on experience, location, and qualifications. Performance-based bonus opportunities. Comprehensive health and wellness benefits. Fully remote work environment with flexibility and autonomy. Opportunity to work on innovative AI-powered and data-driven products at enterprise scale. High visibility and ownership within a strategic product area. Collaborative, cross-functional, and mission-driven work culture. Career growth opportunities within a rapidly evolving product organization. Inclusive workplace committed to equal opportunity and providing reasonable accommodations throughout the hiring process and employment lifecycle. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Senior Product Manager, Customer Insights. Skills: Product strategy, Roadmap development, Analytics, Reporting, Data products, AI-powered insights. Define product strategy. Execute product strategy", "postedDate" : "2026-06-15T08:54:19.604", "createdAt" : "2026-06-15T08:54:19.604", "lastUpdated" : "2026-06-16T13:03:47.596", "ingestTimestamp" : "2026-06-16T03:23:34.741", "mongoId" : "6a30511af292fd229cefa48c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Analytics", "Reporting", "Business intelligence", "Data products", "Data models", "Instrumentation strategies", "Key metrics", "Reporting frameworks", "Data pipelines", "Aggregation strategies", "Data quality", "Scalability", "AI technologies", "Conversational analytics", "Proactive recommendations", "Intelligent workflows", "Audit capabilities", "Governance capabilities", "Product strategy", "Roadmap development", "AI-powered insights", "Data modeling", "Scalability considerations", "Product-market fit", "Cross-functional leadership", "Roadmap planning", "Customer Insights", "AI-native analytics", "Insight-driven experiences", "Enterprise administration", "Governance", "Identity management", "Security", "Compliance", "Audit" ], "skillCount" : 35, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a30511af292fd229cefa48d", "title" : "Senior Product Manager, Customer Insights", "industry" : "Product", "salary" : { "min" : 75000.0, "max" : 110000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Product Manager in the Technology industry in Bulgaria, adjusted for seniority and remote work." }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T14:16:35.966", "fingerprint" : "56e8fa47f44e1c7b8c9c002705dc5ea8b623e0e0632b525829b26b2b7fa2b4b0", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/9d2c7764-9446-41ad-b871-65cc97ea5795/apply", "externalId" : "9d2c7764-9446-41ad-b871-65cc97ea5795", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 4, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, Natural language processing", "professionalSkills" : [ "Roadmap development", "Prioritization", "Data architecture", "Metrics design", "Analytical frameworks", "Stakeholder management", "Cross-functional collaboration", "Product strategy" ], "hardSkillsList" : [ "Data modeling", "Instrumentation strategies", "Metrics design", "Data pipelines", "Analytical frameworks", "API design" ], "hardSkills" : [ { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Instrumentation strategies", "level" : "intermediate" }, { "name" : "Metrics design", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Analytical frameworks", "level" : "intermediate" }, { "name" : "API design", "level" : "intermediate" } ], "majorSkills" : "Customer Insights, Data Products, AI-powered insights", "majorSkillsList" : [ "Customer Insights", "Data Products", "AI-powered insights" ], "coreResponsibilities" : "Own Customer Insights product area, Define usage data architecture, Ensure data quality, Ensure data scalability, Align business metrics, Design reporting experiences, Enhance analytics experiences, Design dashboard experiences, Enhance audit logs experiences, Design API experiences, Drive AI-powered insights vision, Implement AI-powered insights, Collaborate with Sales teams, Collaborate with Customer Success teams, Translate insights into narratives, Engage with enterprise stakeholders, Understand stakeholder needs, Validate stakeholder priorities, Ensure solutions meet requirements, Partner with adjacent product teams, Create seamless experiences, Transform business questions, Develop user-centric solutions", "teamCollaboration" : "Cross-functional collaboration; Work with engineering teams; Work with data teams; Partner with adjacent product teams; Collaborate with Sales teams; Collaborate with Customer Success teams", "projectManagementSkills" : [ "Roadmap development", "Prioritization" ], "domainKnowledge" : "Customer retention; Customer growth; Value measurement; Enterprise administrators; AI-native user experiences; Intelligent analytics; Governance requirements; Compliance requirements; Operational requirements; Identity management; Security domains; Compliance domains; Enterprise analytics", "domainList" : [ "customer-retention", "customer-growth", "value-measurement", "enterprise-administrators", "ai-native-user-experiences", "intelligent-analytics", "governance-requirements", "compliance-requirements", "operational-requirements", "identity-management", "security-domains", "compliance-domains", "enterprise-analytics" ], "domainSpecificKnowledge" : [ "Customer retention", "Customer growth", "Value measurement", "Enterprise administrators", "AI-native user experiences", "Intelligent analytics", "Governance requirements", "Compliance requirements", "Operational requirements", "Identity management", "Security domains", "Compliance domains", "Enterprise analytics" ], "communicationSkills" : "Stakeholder management; Customer narratives", "innovationCreativity" : "AI-powered insights capabilities", "problemSolvingSkills" : "Transform complex business questions", "outcomesObjectives" : "Support customer renewals; Support expansion opportunities; Meet governance requirements; Meet compliance requirements; Meet operational requirements", "qualificationsBasic" : "4+ years product management experience, 2+ years building analytics/reporting/BI/data products, Expertise in data products, Experience with data modeling, Experience with instrumentation strategies, Experience with metrics design, Experience with data pipelines, Experience with analytical frameworks, Ability to work with engineering teams, Ability to work with data teams, Experience developing AI-enabled products, Proven success translating business needs, Experience partnering with customer-facing teams", "qualificationsPreferred" : "Experience building enterprise administration products, Experience building governance products, Experience building identity management products, Experience building security products, Experience building compliance products, Experience building audit-related products, Background in business intelligence platforms, Background in analytics solutions, Background in data-focused products, Experience designing customer-facing APIs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Own the Customer Insights product area end-to-end, including strategy, roadmap development, prioritization, and execution across data foundations and customer-facing experiences. Define and evolve the underlying usage data architecture, ensuring data quality, scalability, and alignment with business metrics that support customer retention, growth, and value measurement. Design and enhance reporting, analytics, dashboards, audit logs, and API experiences that deliver actionable insights to enterprise administrators, executives, and internal teams. Drive the vision and implementation of AI-powered insights capabilities, including natural language interactions, proactive analytics, and intelligent workflows. Collaborate closely with Sales and Customer Success teams to translate product insights into compelling customer narratives that support renewals and expansion opportunities. Engage directly with enterprise stakeholders to understand needs, validate priorities, and ensure solutions meet governance, compliance, and operational requirements. Partner with adjacent product teams to create seamless experiences across administration, identity management, security, and compliance domains. Transform complex and ambiguous business questions into scalable, user-centric product solutions. Requirements 4+ years of product management experience, including at least 2 years building analytics, reporting, business intelligence, or data-driven products for administrative or business users. Strong expertise in data products, including experience with data modeling, instrumentation strategies, metrics design, data pipelines, and analytical frameworks. Demonstrated ability to work effectively with engineering and data teams while balancing technical considerations such as aggregation, data freshness, granularity, and scalability. Experience developing or contributing to AI-enabled products, with a strong understanding of emerging trends in AI-native user experiences and intelligent analytics. Proven success translating complex business needs into intuitive and impactful product experiences. Experience partnering with customer-facing teams to support customer engagement, retention, and growth initiatives. Exceptional communication, stakeholder management, and cross-functional collaboration skills. Ability to thrive in fast-paced environments and navigate ambiguity with confidence. Preferred Qualifications Experience building enterprise administration, governance, identity management, security, compliance, or audit-related products. Background in business intelligence platforms, analytics solutions, or data-focused products. Experience designing customer-facing APIs for analytics, reporting, or data access use cases. Benefits Competitive base salary ranging from $160,000 to $215,000, depending on location, experience, and qualifications. Performance-based bonus opportunities. Comprehensive benefits package. Opportunity to shape the future of enterprise analytics and AI-driven insights. High-impact role with significant ownership and visibility across the organization. Collaborative and cross-functional work environment. Exposure to enterprise-scale products, customers, and strategic initiatives. Inclusive workplace committed to equal opportunity and reasonable accommodations for individuals with disabilities. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Senior Product Manager, Customer Insights. Skills: Customer Insights, Data Products, AI-powered insights. Own Customer Insights product area. Define usage data architecture", "postedDate" : "2026-06-15T08:52:20.464", "createdAt" : "2026-06-15T08:52:20.464", "lastUpdated" : "2026-06-16T14:16:35.966", "ingestTimestamp" : "2026-06-16T03:25:24.529", "mongoId" : "6a30511af292fd229cefa48d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Data modeling", "Instrumentation strategies", "Metrics design", "Data pipelines", "Analytical frameworks", "API design", "Customer Insights", "Data Products", "AI-powered insights", "Roadmap development", "Prioritization", "Data architecture", "Stakeholder management", "Cross-functional collaboration", "Product strategy", "Customer retention", "Customer growth", "Value measurement", "Enterprise administrators", "AI-native user experiences", "Intelligent analytics", "Governance requirements", "Compliance requirements", "Operational requirements", "Identity management", "Security domains", "Compliance domains", "Enterprise analytics" ], "skillCount" : 28, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a308f6cf292fd229c0aab37", "title" : "Senior Software Engineer - Data Engineering", "company" : "Todyl", "industry" : "Engineering", "salary" : { "min" : 170000.0, "max" : 190000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Denver CO", "locations" : [ "Denver CO" ], "timestamp" : "2026-06-16T11:25:13.278", "fingerprint" : "f47cfe4e756fa8bfb525ea398f2f04580b5e174da67ad0c5345c6f50e848f538", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/todyl/ee73c735-6fe5-4877-95bf-62ef4df1943a/application", "externalId" : "ee73c735-6fe5-4877-95bf-62ef4df1943a", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Denver", "state" : "Colorado", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "39.7392364,-104.9848620" } ], "locationText" : "Denver, Colorado, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "remoteFriendly" : true, "rawDescription" : "Todyl puts world-class networking and security within reach of every business. The Todyl Security Platform converges SASE, SIEM, Endpoint Security, GRC, MXDR, and more into a cloud-native, single-agent platform specifically built for MSPs, MSSPs, and Mid-Market IT Professionals. We are a fast-paced, dynamic start-up, passionate about simplifying complex networking and security for businesses of all sizes. About the Role We are looking for a talented, collaborative individual who is deeply knowledgeable in software engineering and enjoys working across many layers of the stack. This will be an opportunity to work on end-to-end development, from design to implementation of our products & services. This position will be involved with developing data ingestion and database systems. The ideal candidate is excited by developing products & solutions supporting large scale data engineering work. Responsibilities - Write efficient, scalable, and high-performance code to meet the demands of our software applications, optimizing algorithms and data structures for speed and reliability. - Design and implement elastic code architectures that enable our software systems to scale horizontally and vertically in response to changing demands. - Architect and implement scalable and reliable data storage solutions to meet the organization's needs. - Work closely with the AI/ML team providing format appropriate data delivery in support of business intelligence initiatives. - Evaluate and select appropriate storage technologies, databases, and data warehouses to meet the organization's needs for data retention, archival, and analysis. - Design and implement data ingestion pipelines to pull data from various sources into ElasticSearch for real-time analytics, search, and visualization. - Optimize data ingestion workflows for scalability, reliability, and fault tolerance, considering high volume and velocity of incoming data streams. - Collaborate with cross-functional teams to integrate data pipelines with the organization's portal and user interfaces, enabling seamless data access and visualization for end users. Requirements - 5+ years of end-to-end commercial software and application development - 2+ years of commercial software development for a multi-tenant cloud platform - Software development experience using Go, JavaScript, HTML - Software development experience under Linux or Unix-based systems - Strong problem-solving skills and ability to adapt existing systems to fast-changing requirements - Ability to thrive in a fast-paced startup environment challenging norm - Optimize data ingestion workflows for scalability, reliability, and fault tolerance, considering high volume and velocity of incoming data streams. - Collaborate with cross-functional teams to integrate data pipelines with the organization's portal and user interfaces, enabling seamless data access and visualization for end users. Todyl provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, transgender status, gender identity or expression, national origin, age, disability, marital status, genetic information, military status or any other status protected by applicable federal, state or local laws. ", "summaryDescription" : "Senior Software Engineer - Data Engineering at Todyl", "createdAt" : "2026-06-16T02:00:24.256", "lastUpdated" : "2026-06-16T11:25:13.278", "ingestTimestamp" : "2026-06-16T02:00:24.256", "mongoId" : "6a308f6cf292fd229c0aab37", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 170000, "salaryAnnualMax" : 190000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a305119f292fd229cef9c97", "title" : "Lead Product Manager, Data and AI", "industry" : "Product", "salary" : { "min" : 85000.0, "max" : 130000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Lead Product Manager, Data and AI in Bulgaria, adjusted for SaaS industry and remote work." }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T13:00:21.262", "fingerprint" : "82fe4f4fdc8ab1372055aa6158ae911736d6dc6afa73b5b74d4c6341bc3b8381", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/f4b9f71e-4327-4077-a695-5a7cf7ad3271/apply", "externalId" : "f4b9f71e-4327-4077-a695-5a7cf7ad3271", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Machine learning, Generative AI, Large language models, LLMs, Advanced analytics", "professionalSkills" : [ "Product strategy", "Roadmap development", "Product lifecycle management", "Stakeholder management", "Product requirements", "Data-driven decision making" ], "hardSkillsList" : [ "AI development", "Analytics solutions", "Product performance measurement", "Experimentation frameworks" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "AI development", "level" : "intermediate" }, { "name" : "Analytics solutions", "level" : "intermediate" }, { "name" : "Product performance measurement", "level" : "intermediate" }, { "name" : "Experimentation frameworks", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine learning, Generative AI, Analytics solutions", "majorSkillsList" : [ "Machine learning", "Generative AI", "Analytics solutions" ], "coreResponsibilities" : "Define product vision and roadmap, Execute product vision and roadmap, Align initiatives with business objectives, Lead development of AI solutions, Lead deployment of AI solutions, Manage product lifecycle, Collaborate with cross-functional stakeholders, Integrate intelligent capabilities into products, Establish frameworks for measuring product performance, Establish frameworks for experimentation, Establish frameworks for business impact, Use data-driven insights for decision-making, Use data-driven insights for optimization, Translate business challenges into product requirements, Act as bridge between technical and non-technical stakeholders, Promote responsible AI development, Partner with governance stakeholders, Partner with privacy stakeholders, Partner with compliance stakeholders, Ensure ethical product outcomes, Ensure secure product outcomes, Ensure reliable product outcomes, Mentor team members, Contribute to product management best practices, Foster culture of innovation, Foster culture of collaboration, Foster culture of continuous improvement", "teamCollaboration" : "Cross-functional stakeholders; Product teams; Engineering teams; Design teams; Operations teams; Business teams; Multidisciplinary teams", "projectManagementSkills" : [ "Roadmap development", "Prioritization", "Execution" ], "domainKnowledge" : "Machine learning concepts; Generative AI technologies; Large language models; LLMs; Advanced analytics; AI infrastructure; Data privacy; Data governance; AI security; Ethical AI principles", "domainList" : [ "machine-learning-concepts", "generative-ai-technologies", "large-language-models", "llms", "advanced-analytics", "ai-infrastructure", "data-privacy", "data-governance", "ai-security", "ethical-ai-principles" ], "domainSpecificKnowledge" : [ "Machine learning concepts", "Generative AI technologies", "Large language models", "LLMs", "Advanced analytics", "AI infrastructure", "Data privacy", "Data governance", "AI security", "Ethical AI principles" ], "communicationSkills" : "Explain technical concepts; Explain trade-offs", "continuousLearning" : "Product management best practices", "innovationCreativity" : "Culture of innovation", "problemSolvingSkills" : "Navigate ambiguity; Prioritize competing objectives; Execute complex initiatives", "qualificationsBasic" : "Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline, 8+ years of product management experience within enterprise SaaS, cloud software, technology, or highly regulated industries, At least 3 years of hands-on experience launching and scaling machine learning, AI, or data-driven products, Deep understanding of machine learning concepts, generative AI technologies, large language models (LLMs), advanced analytics, and the infrastructure required to support AI solutions, Proven ability to develop product strategies, navigate ambiguity, prioritize competing objectives, and successfully execute complex initiatives, Experience working across multidisciplinary teams in fast-paced environments", "qualificationsPreferred" : "Familiarity with regulated industries, Understanding of data privacy, governance, security, and ethical AI principles", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Define and execute a multi-year product vision and roadmap for data and AI platforms, aligning initiatives with business objectives, growth strategies, and operational priorities. Lead the development and deployment of advanced AI, machine learning, generative AI, and analytics solutions, managing the full product lifecycle from ideation and experimentation to scalable production delivery. Collaborate closely with cross-functional stakeholders across product, engineering, design, operations, and business teams to integrate intelligent capabilities into core products and workflows. Establish frameworks for measuring product performance, experimentation, and business impact, using data-driven insights to guide decision-making and optimization efforts. Translate complex business challenges into clear product requirements and act as a bridge between technical specialists and non-technical stakeholders. Promote responsible AI development by partnering with governance, privacy, and compliance stakeholders to ensure ethical, secure, and reliable product outcomes. Mentor team members, contribute to product management best practices, and help foster a culture of innovation, collaboration, and continuous improvement. Requirements Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline. 8+ years of product management experience within enterprise SaaS, cloud software, technology, or highly regulated industries, with a strong track record of delivering large-scale products. At least 3 years of hands-on experience launching and scaling machine learning, AI, or data-driven products. Deep understanding of machine learning concepts, generative AI technologies, large language models (LLMs), advanced analytics, and the infrastructure required to support AI solutions. Proven ability to develop product strategies, navigate ambiguity, prioritize competing objectives, and successfully execute complex initiatives. Strong communication and stakeholder management skills, with the ability to explain technical concepts and trade-offs to executive and non-technical audiences. Experience working across multidisciplinary teams in fast-paced environments and influencing decisions without direct authority. Familiarity with regulated industries and an understanding of data privacy, governance, security, and ethical AI principles is considered a strong advantage. Benefits Annual base salary ranging from $161,000 to $221,500, depending on experience, qualifications, and location. Eligibility for performance-based or discretionary bonus programs. Comprehensive healthcare coverage, including medical, dental, vision, life, and disability insurance options. Flexible spending accounts (FSA) and health savings account (HSA) programs. Access to coaching, therapy, and well-being support services. Equity participation through company stock programs. Generous paid time off, including vacation, sick leave, and company holidays. Paid parental leave. 401(k) retirement plan with company matching contributions. Monthly technology allowance. Additional wellness initiatives, employee events, recognition programs, and community-focused activities. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Lead Product Manager, Data and AI. Skills: Machine learning, Generative AI, Analytics solutions. Define product vision and roadmap. Execute product vision and roadmap", "postedDate" : "2026-06-15T09:26:38.520", "createdAt" : "2026-06-15T09:26:38.520", "lastUpdated" : "2026-06-16T13:00:21.262", "ingestTimestamp" : "2026-06-16T03:24:32.331", "mongoId" : "6a305119f292fd229cef9c97", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "AI development", "Analytics solutions", "Product performance measurement", "Experimentation frameworks", "Leadership", "Mentoring", "Machine learning", "Generative AI", "Product strategy", "Roadmap development", "Product lifecycle management", "Stakeholder management", "Product requirements", "Data-driven decision making", "Prioritization", "Execution", "Machine learning concepts", "Generative AI technologies", "Large language models", "LLMs", "Advanced analytics", "AI infrastructure", "Data privacy", "Data governance", "AI security", "Ethical AI principles" ], "skillCount" : 26, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3079aef292fd229c0343d8", "title" : "Principal Software Engineer, Data Engineering", "company" : "Highspot", "industry" : "Engineering", "salary" : { "min" : 250000.0, "max" : 350000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Principal Software Engineer in Seattle, adjusted for the SaaS industry and executive seniority level." }, "location" : "Seattle", "locations" : [ "Seattle" ], "timestamp" : "2026-06-16T15:08:38.625", "fingerprint" : "97b85fa49e6386a6f9a2114f90be281b7e32495458e8d358ee1541ddb99484ec", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/highspot/c49beaf1-a5fe-4883-865a-d8885fbef5df/apply", "externalId" : "c49beaf1-a5fe-4883-865a-d8885fbef5df", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 10, "experienceMaxYears" : 99, "experienceLevel" : "Principal", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "## Description About Highspot Highspot is pioneering the category that is fundamentally changing the way companies increase sales productivity. On a mission to transform the way millions of people work with sales enablement, Highspot is committed to building breakthrough software with a spark of magic. We believe a great place to work is about more than the work – it’s about what the company stands for, and how it authentically represents its values in the real world. To this end, we have put intentional focus on creating equitable workspaces for each of our employees. Our goal is to create a culture where everyone feels a deep sense of belonging and is empowered to be an agent of change, with the ability to transform themselves, their workplace, and their world. About the Role We are looking for a Principal Data Engineer to join our growing Data Platform team. This is a rare opportunity to define the technical vision for high-scale data products that power customer-facing analytics, intelligent AI agents, and core product capabilities. Highspot's data engineering challenges are uniquely interesting: our platform generates rich, deeply nested document-oriented data from millions of enterprise interactions – content engagement, CRM activity, sales workflows – and our job is to make all of it available, trustworthy, and fast for radically different consumption patterns. Customer-facing analytics dashboards need pre-aggregated, low-latency reads. Scorecards and reports need flexible dimensional models. AI agents need fresh, contextually assembled data with retrieval characteristics that look nothing like traditional BI. You'll own the architecture that serves all three from a unified foundation. As a Principal Data Engineer, you will shape our overarching data architecture direction and fundamentally influence our data strategy. Your impact will extend well beyond your immediate crew – acting as a vital bridge that coordinates directly with upstream software engineering teams (data producers) as well as downstream engineering and AI teams (data consumers) across multiple organizational pillars. You will lead the technical execution of a high-performing engineering crew, balancing deep architectural pipeline design with advanced data modeling, query optimization, and data trust. ## What You'll Do Architect the data platform – drive the technical direction for a scalable, reliable data platform built on a medallion architecture that serves customer-facing analytics, reporting, and agentic AI from a unified foundation. Build and optimize ingestion pipelines – design robust CDC, real-time streaming (Kafka, Flink), and batch processing pipelines that transform complex, nested document-oriented operational data into clean analytical models at enterprise scale. Tame schema complexity – build resilient ingestion and transformation layers that gracefully handle deeply nested, continuously evolving document schemas — deciding where to absorb complexity (ingestion, transformation, or query time) and making those tradeoffs explicit and sustainable. Serve AI and analytics consumption patterns – architect data products that support both traditional BI workloads (pre-aggregated dashboards, dimensional models for scorecards and reports) and emerging AI consumption patterns (low-latency retrieval, contextual assembly, freshness-sensitive agent queries). Own data quality, contracts, and observability – establish the data trust infrastructure that makes cross-team data consumption reliable: schema contracts with upstream producers, data quality monitoring, lineage tracking, freshness SLAs, and clear escalation paths when things break. Drive cost-aware architecture – own Snowflake warehouse optimization, compute governance, and cost-efficient pipeline design. Build the practices and visibility so the team makes principled cost/performance tradeoffs rather than discovering them on the invoice. Bridge producers and consumers – collaborate across organizational boundaries to align upstream software engineering teams and downstream analytics and AI teams around unified data strategies, shared contracts, and engineering standards. Lead and grow the team – technically lead and growth-coach a diverse crew of data engineers. Champion best practices across the full spectrum of data engineering disciplines, from low-level pipeline architecture to sophisticated data modeling and analytical query performance. ## Your Background What will set you apart: Demonstrated depth in building production data platforms that serve multiple consumption patterns – you've gone beyond traditional BI to support real-time product features, AI/ML workloads, or customer-facing analytics from the same data foundation. Deep experience with the impedance mismatch between document-oriented operational stores and analytical systems – you've dealt with nested, schema-evolving source data (MongoDB, DynamoDB, or similar) and have opinions on where flattening and transformation should live. Hands-on experience with data quality and trust at scale – you've built or operated schema registries, data contracts, quality monitoring, or lineage systems in an environment where multiple teams depend on shared data products. Track record of cost-conscious data architecture – you've optimized Snowflake (or comparable) warehouse spend, designed compute governance policies, or re-architected pipelines to materially reduce cost without sacrificing reliability. Strong instinct for the bridge role: you're as comfortable pushing back on an upstream team's schema change as you are negotiating freshness SLAs with a downstream AI consumer. Foundations: 8+ years of professional software engineering experience, with significant time spent on distributed, data-intensive production systems – including substantial depth in data pipeline and platform architecture. Deep hands-on expertise with modern data technologies: Snowflake, Apache Kafka, Apache Flink, and CDC tooling (Debezium or similar). Experience developing and operating cloud data infrastructure at enterprise scale (AWS preferred), including infrastructure-as-code (Terraform) and CI/CD automation. Strong programming skills in Python, Java, and SQL. You write production-grade code, not just scripts. A track record of designing performant data models that support fast, efficient querying for analytical and product-facing use cases. Strong cross-functional communication skills - you work effectively with software engineers, data scientists, AI teams, and business stakeholders across organizational boundaries. Experience mentoring engineers and building collaborative, high-performing teams. ## Additional Information Base salary range: $188,696 - $258,391 Employees may also be eligible for bonuses and other forms of compensation. The above represents total expected compensation for this role. Actual compensation will depend on various job-related factors, including, but not limited to, location, experience, and job qualifications. Highspot also offers the following employee benefits for this position: -Comprehensive medical, dental, vision, disability, and life benefits -Health Savings Account (HSA) with employer contribution -401(k) Matching with immediate vesting on employer match -Flexible PTO -8 paid holidays and 5 paid days for Annual Holiday Week -Quarterly Recharge Fridays (paid days off for mental health recharge) -18 weeks paid parental leave -Access to Coaches and Therapists through Modern Health -2 volunteer days per year -Commuting benefits #LI-DL1 Equal Opportunity Statement We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of age, ancestry, citizenship, color, ethnicity, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or invisible disability status, political affiliation, veteran status, race, religion, or sexual orientation. Did you read the requirements as a checklist and not tick every box? Don't rule yourself out! If this role resonates with you, hit the ‘apply’ button.", "summaryDescription" : "Principal Software Engineer, Data Engineering at Highspot", "postedDate" : "2026-06-15T18:22:09.012", "createdAt" : "2026-06-15T18:22:09.012", "lastUpdated" : "2026-06-16T15:08:38.625", "ingestTimestamp" : "2026-06-16T03:26:02.807", "mongoId" : "6a3079aef292fd229c0343d8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 250000, "salaryAnnualMax" : 350000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "68c2e43bf8b1b0376634c92a", "title" : "Business Intelligence Engineer, P2 Science, Data, and Insights", "company" : "Amazon Development Centre Canada ULC", "industry" : "Business Intelligence, Business Intel Engineer, north america stores", "salary" : { "min" : 76400.0, "max" : 127600.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, CAN", "locations" : [ "Vancouver, British Columbia, CAN" ], "timestamp" : "2026-06-15T01:05:27.815", "fingerprint" : "3a1dff98e3fb79510c323d58b42de9415775c735f6b151a142ee0971a1f86454", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3071381/apply", "externalId" : "67764e7e-19dd-455a-93dc-f5db067e6670", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "Redshift, Oracle, NoSQL, Tableau, Quicksight, R, SAS, Matlab, Python, AWS, EC2, DynamoDB, S3", "professionalSkills" : [ "Business intelligence", "Pricing strategy", "Promotions strategy", "Data modeling", "ETL pipelines", "Anomaly detection", "Business strategy", "Data visualization", "Data infrastructure", "Data quality" ], "hardSkillsList" : [ "Data analysis", "Data visualization", "Data modeling", "ETL", "Statistical analysis", "SQL", "Python scripting" ], "softSkillsList" : [ "Curiosity", "Customer obsession", "Entrepreneurial spirit" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Data visualization", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "ETL", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "SQL", "level" : "intermediate" }, { "name" : "Python scripting", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Curiosity" }, { "name" : "Customer obsession" }, { "name" : "Entrepreneurial spirit" } ], "majorSkills" : "Business intelligence, Data engineering, Analytics", "majorSkillsList" : [ "Business intelligence", "Data engineering", "Analytics" ], "coreResponsibilities" : "Spearhead business intelligence initiatives, Develop analytical metrics and models, Present insights and recommendations, Harness LLMs for insights, Lead data-driven discussions, Pioneer new methodologies, Design automated reporting systems, Create intuitive dashboards, Innovate and simplify tools, Enhance back-end data sources, Implement data quality practices, Architect scalable data solutions, Craft narratives from data, Develop effective metrics, Collaborate across teams, Champion innovation culture, Stay at forefront of BI trends, Mentor colleagues", "teamCollaboration" : "Product teams; Cross-functional teams", "domainKnowledge" : "Pricing; Promotions; Retail pricing; Customer behavior; Market dynamics", "domainList" : [ "pricing", "promotions", "retail-pricing", "customer-behavior", "market-dynamics" ], "domainSpecificKnowledge" : [ "Pricing", "Promotions", "Retail pricing", "Customer behavior", "Market dynamics" ], "toolProficiency" : [ "Tableau", "Quicksight", "R", "SAS", "Matlab", "Python" ], "communicationSkills" : "Presenting insights; Crafting narratives", "continuousLearning" : "Learning new technologies", "innovationCreativity" : "Innovate; Pioneer new methodologies; Simplify tools; Innovation culture", "problemSolvingSkills" : "Solving complex problems; Data-driven decision making", "outcomesObjectives" : "Drive pricing and promotions decisions; Shape business strategy; Enhance customer experience; Drive business growth; Improve accuracy; Streamline operations; Maximize impact", "qualificationsBasic" : "3+ years analyzing data, Experience as BIE, Data visualization experience, Data modeling experience, ETL pipeline experience, Statistical Analysis experience, Develop new metrics, SQL data pulling, Python scripting experience, Bachelors Degree", "qualificationsPreferred" : "AWS solutions experience, Data mining experience, Large-scale datasets experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Shape How Amazon Serves Millions Through Pricing and Promotions Ready to transform how customers experience Amazon? Join our Pricing & Promotions Science, Data, and Insights team, where your analytical expertise will directly influence pricing and promotions decisions that impact millions of customers globally. Your Impact As a Business Intelligence Engineer, you'll be at the heart of Amazon's data-driven culture, building automated analytics tools that power intelligent pricing and promotions decisions. Your insights will shape strategy, drive customer satisfaction, and influence business growth across one of Amazon's most critical functions. What Makes You a Great Fit - You're a hands-on engineer who thrives on solving complex problems - You have an insatiable curiosity and love learning new technologies - You see opportunities where others see challenges - You build trust through delivery and customer obsession - You bring an entrepreneurial spirit to everything you do What You'll Create - Automated analytics systems that drive pricing and promotions decisions - Sophisticated anomaly detection tools - Data-driven insights that shape business strategy - Solutions that simplify complex problems - Tools that enhance customer experience Why This Role - Direct impact on Amazon's core business decisions - Opportunity to innovate in a fast-paced environment - Work with advanced analytics technologies - Shape the future of retail pricing and promotions - Join a team that values curiosity and creativity Transform data into decisions that matter. Join us in making Amazon the most customer-centric company through intelligent pricing solutions. Key job responsibilities Drive Strategic Insights - Spearhead business intelligence initiatives that directly impact Amazon's pricing and promotions strategy - Develop advanced analytical metrics and models to uncover hidden business opportunities - Present compelling insights and recommendations to senior leadership, influencing key decisions Innovate with Advanced Analytics - Harness the power of Large Language Models (LLMs) to generate business impacting insights - Lead data-driven discussions with Product teams to accelerate growth - Pioneer new methodologies in pricing and promotions analytics, setting industry standards Build Scalable Solutions - Design and implement automated reporting systems that drive efficiency - Create intuitive dashboards that transform complex data into clear, actionable insights - Continuously innovate and simplify tools and processes, maximizing impact Optimize Data Infrastructure - Enhance back-end data sources to improve accuracy and streamline operations - Implement best practices in data quality and modeling - Architect scalable data solutions that grow with the business Influence Through Communication - Craft compelling narratives from data, influencing key stakeholders - Develop effective metrics that shape the future of Amazon's pricing and promotions - Collaborate across teams to drive adoption of data-driven strategies Lead Continuous Improvement - Champion a culture of innovation, constantly seeking ways to improve and automate - Stay at the forefront of BI trends, bringing developing technologies to the team - Mentor colleagues in advanced analytics techniques, elevating team capabilities In this role, you'll be at the forefront of shaping how Amazon prices and promotes products globally. Your analytical expertise will directly impact customer experience and business growth, making you a key player in Amazon's mission to be Earth's most customer-centric company. About the team The Pricing and Promotions (P2) Science, Data and Insights team is at the forefront of Amazon's data revolution, orchestrating a sophisticated ecosystem with hundreds of PBs of data and thousands of active datasets that empower business leaders to create exceptional customer experiences through data-driven pricing and promotional strategies. Our team combines deep engineering expertise with business acumen to manage mission-critical data and insights that influence billions in revenue decisions, while pioneering innovative approaches that transform how Amazon understands customer behavior and market dynamics. Our strength comes from the diverse perspectives and backgrounds of our team members, who bring unique problem-solving approaches to these complex challenges. We're currently implementing an ambitious three-year transformation strategy that will fundamentally reshape how Amazon makes pricing and promotional decisions, focusing on intelligent automation and proactive insights that drive business outcomes. Beyond managing science, data, and insights, we're true strategic partners who translate complex information into actionable intelligence that shapes Amazon's direction across global marketplaces. If you're passionate about solving complex business problems at massive scale while working in a collaborative culture that values both analytical rigor and business impact, you'll find compelling opportunities to grow and make a meaningful difference on our team. Basic Qualifications: - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - Experience working as a BIE in a technology company - Experience with data visualization using Tableau, Quicksight, or similar tools - Experience with data modeling, warehousing and building ETL pipelines - Experience in Statistical Analysis packages such as R, SAS and Matlab - Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling - Bachelors Degree Preferred Qualifications: - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary for this position ranges from $76,400/year up to $127,600/year. Salary is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. Applicants should apply via our internal or external career site.", "summaryDescription" : "Business Intelligence Engineer, P2 Science, Data, and Insights at Amazon Development Centre Canada ULC. Skills: Business intelligence, Data engineering, Analytics. Spearhead business intelligence initiatives. Develop analytical metrics and models", "postedDate" : "2026-06-13T08:30:29.501", "createdAt" : "2026-06-13T08:30:29.501", "lastUpdated" : "2026-06-15T01:05:27.815", "ingestTimestamp" : "2026-06-13T08:30:29.501", "mongoId" : "68c2e43bf8b1b0376634c92a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3071381/apply", "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Data analysis", "Data visualization", "Data modeling", "ETL", "Statistical analysis", "SQL", "Python scripting", "Curiosity", "Customer obsession", "Entrepreneurial spirit", "Business intelligence", "Data engineering", "Analytics", "Pricing strategy", "Promotions strategy", "ETL pipelines", "Anomaly detection", "Business strategy", "Data infrastructure", "Data quality", "Pricing", "Promotions", "Retail pricing", "Customer behavior", "Market dynamics", "Tableau", "Quicksight", "R", "SAS", "Matlab", "Python" ], "skillCount" : 31, "jobCategory" : "other", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a21770d74d8ee00a0c1ba39", "title" : "SDE-II, AI Core Infra - AI Analytics and Insights", "company" : "ADCI", "industry" : "Software Development, Advertising", "salary" : { "min" : 2200000.0, "max" : 3500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for SDE-II in Bengaluru, India, adjusted for mid-seniority and technology industry." }, "location" : "Bengaluru, Karnataka, IND", "locations" : [ "Bengaluru, Karnataka, IND" ], "timestamp" : "2026-06-15T05:51:21.918", "fingerprint" : "371ada8374f4ce90a8134beb6044ec338491e49d186dd75df17adae08e1fbb80", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10435578/apply", "externalId" : "79a35f46-1a86-44b5-939b-41b83b4109c4", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Generative AI, LLMs, RAG, NLP, NLU, SQL, Python, C#, C++, Java, Perl, Object Oriented Design", "professionalSkills" : [ "System design", "Architecture", "Data engineering", "Conversational interfaces", "AI-powered systems" ], "hardSkillsList" : [ "Data structures", "Algorithms", "Large-scale computing", "Vector stores", "Embedding pipelines", "Metadata indexing", "Prompt management", "Model routing", "Multi-agent orchestration", "Chain-of-thought workflows", "SQL generation", "Metadata auto-curation" ], "softSkillsList" : [ "Ownership", "Ambiguity" ], "hardSkills" : [ { "name" : "Data structures", "level" : "intermediate" }, { "name" : "Algorithms", "level" : "intermediate" }, { "name" : "Large-scale computing", "level" : "intermediate" }, { "name" : "Vector stores", "level" : "intermediate" }, { "name" : "Embedding pipelines", "level" : "intermediate" }, { "name" : "Metadata indexing", "level" : "intermediate" }, { "name" : "Prompt management", "level" : "intermediate" }, { "name" : "Model routing", "level" : "intermediate" }, { "name" : "Multi-agent orchestration", "level" : "intermediate" }, { "name" : "Chain-of-thought workflows", "level" : "intermediate" }, { "name" : "SQL generation", "level" : "intermediate" }, { "name" : "Metadata auto-curation", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Ownership" }, { "name" : "Ambiguity" } ], "majorSkills" : "Generative AI, Conversational AI, Data Engineering, LLM Integration", "majorSkillsList" : [ "Generative AI", "Conversational AI", "Data Engineering", "LLM Integration" ], "coreResponsibilities" : "Design scalable services, Build scalable services, Engineer RAG architectures, Build embedding pipelines, Optimize vector stores, Integrate LLMs, Operationalize LLMs, Build automated evaluation, Design feedback loops, Develop SQL generation, Develop SQL validation, Build metadata auto-curation tools, Productionize NLP/NLU models, Integrate NLP/NLU models, Own systems end-to-end, Monitor production environment, Improve prompt templates", "teamCollaboration" : "Applied scientists; Product managers; Fellow engineers", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "Advertising data lake; Conversational AI; Generative AI; Data retrieval; Large-scale computing; Multi-tiered systems; Embedded systems; Distributed software", "domainList" : [ "advertising-data-lake", "conversational-ai", "generative-ai", "data-retrieval", "large-scale-computing", "multi-tiered-systems", "embedded-systems", "distributed-software" ], "domainSpecificKnowledge" : [ "Advertising data lake", "Conversational AI", "Generative AI", "Data retrieval", "Large-scale computing", "Multi-tiered systems", "Embedded systems", "Distributed software" ], "toolProficiency" : [ "Amazon Web Services" ], "communicationSkills" : "Design reviews", "innovationCreativity" : "Invent new experiences", "problemSolvingSkills" : "Troubleshooting", "outcomesObjectives" : "Generate insights faster; Ensure accurate retrieval; Drive system improvement; Ensure trusted outputs; Maintain metadata catalog", "qualificationsBasic" : "3+ years professional software development, 2+ years system design/architecture, 1+ years large-scale software development, 1+ years Object Oriented Design, Experience with C#, C++, Java, or Perl, Programming with one language", "qualificationsPreferred" : "4+ years full SDLC experience, Bachelor's degree in computer science", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising solutions that drive product discovery and sales. We deliver billions of ad impressions every single day on behalf of our advertisers and generate massive volumes of data across the advertising lifecycle. We are building a conversational AI assistant that empowers data engineers, analysts, and business stakeholders to interact with our vast advertising data lake through natural language. Using state-of-the-art generative AI, SpektrBot enables teams to generate insights faster by translating natural language queries into accurate, trusted data retrievals, eliminating the friction between questions and answers. As an SDE II on this team, you will be at the center of designing, building, and scaling the systems that power this conversational AI experience. You will architect robust backend services, build reliable integrations with large language models (LLMs), develop retrieval-augmented generation (RAG) pipelines, and engineer the feedback loops that allow our system to continuously evaluate and improve itself. You will work alongside applied scientists, product managers, and fellow engineers in a fast-paced, high-ownership environment where your contributions directly shape the product and influence how thousands of internal customers interact with data. This is a rare opportunity to build a 0-to-1 product at Amazon's scale, one that sits at the intersection of generative AI, data engineering, and conversational interfaces. If you are passionate about building production-grade AI-powered systems, thrive in ambiguity, and want to see your work used every day by teams across Amazon Advertising, we'd love to talk to you. At Amazon an SDE can expect to design flexible and scalable solutions, and work on some of the most complex challenges in large-scale computing by utilizing your skills in data structures, algorithms, and object oriented programming. Coming to Amazon gives you the opportunity to work on a small development team in one of our many organizations; Amazon Web Services, ecommerce Services, Kindle, Marketplace, Operations, Platform Technologies and Retail. Key job responsibilities - Design and build scalable services that power SpektrBot's conversational AI platform, including query orchestration, context management, session handling, and response generation pipelines - Engineer RAG architectures — build and optimize retrievers, vector stores, embedding pipelines, and metadata indexing systems to ensure accurate and contextually relevant data retrieval from our advertising data lake - Integrate and operationalize LLMs — build the infrastructure for prompt management, model routing, multi-agent orchestration, and chain-of-thought workflows that enable natural, multi-turn conversations - Build automated evaluation and feedback loops — design systems that continuously measure response accuracy, detect regressions, and feed corrections back into the system to drive improvement over time - Develop SQL generation and validation pipelines — engineer the end-to-end flow from natural language intent to generated SQL, including guardrails, query validation, and result verification to ensure trusted outputs - Build tooling for metadata auto-curation — create LLM-powered tools that automatically enrich, classify, and maintain the metadata catalog that underpins accurate data retrieval - Collaborate with applied scientists to productionize NLP/NLU models and integrate them into the bot's overall architecture - Own systems end-to-end — from design through deployment, monitoring, alarming, and operational excellence in a production environment serving internal customers at scale A day in the life You might start by reviewing your automated evaluation dashboard, investigating a flagged drop in SQL generation accuracy and shipping a fix. After lunch, you pair with an applied scientist to integrate a new intent classification model into the orchestration layer, ensuring graceful fallback behavior. Later, you lead a design review for a multi-agent architecture that breaks complex user questions into parallel sub-queries. You end the day improving prompt templates based on user feedback patterns. Every day brings a different problem, but the thread is always building AI-powered systems that are accurate, reliable, and delightful to use. About the team You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Basic Qualifications: - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Experience programming with at least one software programming language Preferred Qualifications: - 4+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "SDE-II, AI Core Infra - AI Analytics and Insights at ADCI. Skills: Generative AI, Conversational AI, Data Engineering, LLM Integration. Design scalable services. Build scalable services", "postedDate" : "2026-06-13T14:36:54.588", "createdAt" : "2026-06-13T14:36:54.588", "lastUpdated" : "2026-06-15T05:51:21.918", "ingestTimestamp" : "2026-06-13T14:36:54.588", "mongoId" : "6a21770d74d8ee00a0c1ba39", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10435578/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data structures", "Algorithms", "Large-scale computing", "Vector stores", "Embedding pipelines", "Metadata indexing", "Prompt management", "Model routing", "Multi-agent orchestration", "Chain-of-thought workflows", "SQL generation", "Metadata auto-curation", "Ownership", "Ambiguity", "Generative AI", "Conversational AI", "Data Engineering", "LLM Integration", "System design", "Architecture", "Data engineering", "Conversational interfaces", "AI-powered systems", "Agile", "Advertising data lake", "Data retrieval", "Multi-tiered systems", "Embedded systems", "Distributed software", "Amazon Web Services" ], "skillCount" : 30, "jobCategory" : "engineering", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a307f83f292fd229c05a207", "title" : "Senior Data Scientist, Product, AI Context Engineering", "industry" : "Technology", "salary" : { "min" : 185000.0, "max" : 275000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Data Scientist in Mountain View, adjusted for the technology industry and senior experience level." }, "location" : "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]", "locations" : [ "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T12:39:17.340", "fingerprint" : "ec5f96e8443b72b363ea10fda0498f617f9c560534956496923ed887cfde8581", "source" : "google", "language" : "en", "externalId" : "91207088033669830", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Mountain View", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.3893889,-122.0832101" } ], "locationText" : "Mountain View, California, United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL, Spark, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, SageMaker, GCP, BigQuery, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Statistical analysis", "Machine learning", "Data modelling", "A/B testing", "Causal inference" ], "hardSkillsList" : [ "Regression", "Classification", "Clustering", "Time-series analysis" ], "hardSkills" : [ { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, AI, Data Science", "majorSkillsList" : [ "Machine Learning", "AI", "Data Science" ], "coreResponsibilities" : "Develop and deploy machine learning models, Design and implement data pipelines, Conduct statistical analysis, Build and maintain BI dashboards, Collaborate with product teams, Drive product innovation through AI", "teamCollaboration" : "Cross-functional teams; Product managers; Engineering teams", "domainKnowledge" : "Product analytics; AI context engineering", "domainList" : [ "product-analytics", "ai-context-engineering" ], "domainSpecificKnowledge" : [ "Product analytics", "AI context engineering" ], "toolProficiency" : [ "Dbt", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Present findings; Communicate insights", "documentationSkills" : "Technical documentation", "innovationCreativity" : "Drive product innovation", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "5+ years Python, SQL proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "summaryDescription" : "Senior Data Scientist, Product, AI Context Engineering. Skills: Machine Learning, AI, Data Science. Develop and deploy machine learning models. Design and implement data pipelines", "postedDate" : "2026-06-16T01:49:15.452", "createdAt" : "2026-06-16T01:49:15.452", "lastUpdated" : "2026-06-16T12:39:17.340", "ingestTimestamp" : "2026-06-16T01:49:15.452", "mongoId" : "6a307f83f292fd229c05a207", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 185000, "salaryAnnualMax" : 275000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Regression", "Classification", "Clustering", "Time-series analysis", "Machine Learning", "AI", "Data Science", "Statistical analysis", "Machine learning", "Data modelling", "A/B testing", "Causal inference", "Product analytics", "AI context engineering", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Dbt", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Tableau", "Power BI", "Looker" ], "skillCount" : 26, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.6666667, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "69ce5e3b9bc74574cb677aec", "title" : "T6_Chief Data and AI Architect", "company" : "MBRDI", "industry" : "Manufacturing", "salary" : { "min" : 6000000.0, "max" : 9000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Executive Chief Data and AI Architect in Bangalore, India, adjusted for industry and company size." }, "location" : "India-Karnataka-Bangalore", "locations" : [ "India-Karnataka-Bangalore", "Brigade Tech Gardens, Katha No. 119, Kundalahalli Village, K.R. Puram Hobli, Ward No. 85, Bangalore" ], "certifications" : [ "Azure Data Engineer", "Azure Architect", "AWS Certified Machine Learning" ], "timestamp" : "2026-06-15T10:23:16.352", "fingerprint" : "370e2b00770dd492a2575292193f9eb76fd8365da30dfb9faa3fab6b2d172cdd", "source" : "taleo", "language" : "en", "applyUrl" : "https://daimler.taleo.net/careersection/ex/jobdetail.ftl?job=877618", "externalId" : "877618", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bangalore", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bangalore, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 10, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Data Architecture, Data Engineering, AI, ML, Spark, Dbt, Kafka, Databricks, Synapse, Snowflake, APIs, Python, R, Scala, TensorFlow, PyTorch, Azure ML, SageMaker, Delta Lake, AWS, GCP, Azure", "professionalSkills" : [ "Solution design", "Stakeholder management", "Team leadership", "Thought leadership", "Knowledge sharing", "Technical excellence" ], "hardSkillsList" : [ "Data modeling", "Data ingestion", "Data integration", "Metadata management", "Data lineage", "Data quality", "Model lifecycle management", "Model versioning", "Model monitoring", "Risk assessment" ], "hardSkills" : [ { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "Data integration", "level" : "intermediate" }, { "name" : "Metadata management", "level" : "intermediate" }, { "name" : "Data lineage", "level" : "intermediate" }, { "name" : "Data quality", "level" : "intermediate" }, { "name" : "Model lifecycle management", "level" : "intermediate" }, { "name" : "Model versioning", "level" : "intermediate" }, { "name" : "Model monitoring", "level" : "intermediate" }, { "name" : "Risk assessment", "level" : "intermediate" } ], "majorSkills" : "Data Architecture, AI, ML, Data Engineering", "majorSkillsList" : [ "Data Architecture", "AI", "ML", "Data Engineering" ], "coreResponsibilities" : "Design scalable data architectures, Oversee data ingestion, Oversee data integration, Oversee data transformation, Define metadata best practices, Define data lineage best practices, Define data quality best practices, Lead data model development, Lead data pipeline development, Lead data transformation development, Enable self-serve analytics, Identify AI/ML use cases, Evaluate AI/ML use cases, Design AI solutions, Build AI pipelines, Build ML pipelines, Promote responsible AI, Define AI governance frameworks, Implement AI governance frameworks, Establish model policies, Act as thought leader, Inspire cross-functional teams, Mentor cross-functional teams, Facilitate knowledge sharing, Promote technical excellence, Promote curiosity", "teamCollaboration" : "Cross-functional teams; DevOps teams; Cloud teams; BI teams; Analytics teams; Data Scientists; MLOps engineers; Product owners", "domainKnowledge" : "Data lakehouse; Streaming data; Unstructured data; Structured data; Business intelligence; Analytics engineering; Quantitative analysis; Cloud data stacks; ML frameworks; BI platforms; Statistical methods; Responsible AI; Ethical AI; Model interpretability; GenAI", "domainList" : [ "data-lakehouse", "streaming-data", "unstructured-data", "structured-data", "business-intelligence", "analytics-engineering", "quantitative-analysis", "cloud-data-stacks", "ml-frameworks", "bi-platforms", "statistical-methods", "responsible-ai", "ethical-ai", "model-interpretability", "genai" ], "domainSpecificKnowledge" : [ "Data lakehouse", "Streaming data", "Unstructured data", "Structured data", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "Responsible AI", "Ethical AI", "Model interpretability", "GenAI" ], "toolProficiency" : [ "Dbt Cloud", "Fivetran", "Airflow" ], "communicationSkills" : "Stakeholder communication; Technical concepts communication", "innovationCreativity" : "Innovation", "qualificationsBasic" : "Bachelor's or Master's degree, 10+ years experience, Cloud data platforms experience, AI/ML frameworks knowledge, Governance frameworks experience, Data privacy experience, MLOps experience, Excellent communication skills, Stakeholder management skills, Lead technical teams ability", "qualificationsPreferred" : "AI / GenAI usecase delivery experience, Model interpretability experience, Regulatory compliance experience, Enterprise data modernization experience, AI transformation programs experience, Cloud data architecture certifications, AI certifications", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About MBRDI: Mercedes-Benz Research and Development India (MBRDI), headquartered in Bengaluru with a satellite office in Pune, is the largest R&D center for Mercedes-Benz Group AG outside of Germany. Our mission is to drive innovation and excellence in automotive engineering, digitalization, and sustainable mobility solutions, shaping the future of mobility. We are seeking a visionary Data and AI Chief Architect to lead the design, development, and governance of department wide data and AI solutions. This role requires a balance of deep technical expertise, architectural vision, and the ability to inspire cross-functional teams toward a unified data and AI strategy. As a key member of the architecture and innovation team, you will shape how data is collected, transformed, and leveraged across the organization — enabling scalable data engineering pipelines, responsible AI adoption, and the delivery of intelligent business outcomes. Key Responsibilities 1. Data Architecture & Engineering Design and implement modern, scalable data architectures (data lakehouse, streaming, APIs, etc.) to support analytics and AI workloads. Oversee data ingestion, integration, and transformation processes across structured and unstructured sources. Partner with DevOps and Cloud teams to ensure data platforms meet enterprise performance, security, and compliance standards. Define best practices for metadata management, data lineage, and data quality frameworks. 2. Data Transformation & Analytics Enablement Lead the development of robust data models, pipelines, and transformations using modern tools (e.g., Spark, dbt, Kafka, Databricks, Synapse, Snowflake, etc.). Collaborate with BI and analytics teams to ensure data is clean, contextual, and analytics-ready. Enable business units to self-serve and innovate through governed data products and APIs. 3. AI Use Case Discovery & Delivery Partner with business stakeholders to identify and evaluate high-impact AI/ML use cases. Provide technical leadership in designing AI solutions — from proof of concept to production deployment. Collaborate with Data Scientists and MLOps engineers to build scalable AI and machine learning pipelines. Promote responsible AI practices ensuring transparency, fairness, and explainability in all AI initiatives. 4. AI Governance & Strategy Define and implement frameworks for AI governance, including ethical AI guidelines, model lifecycle management, and compliance. Establish policies for model versioning, monitoring, and risk assessment. Act as a thought leader on AI maturity and innovation across the organization. 5. Cross-Functional Leadership & Inspiration Inspire and mentor cross-functional teams — including engineers, analysts, and product owners — toward data-driven and AI-powered ways of working. Facilitate knowledge sharing and promote a culture of technical excellence and curiosity. Communicate complex technical concepts to non-technical stakeholders effectively. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI, or a related field. 10+ years of experience in data architecture, data engineering, or AI/ML solution design. Proven experience with cloud data platforms (Azure, AWS, or GCP) and modern data stack tools. Strong knowledge of AI/ML frameworks (TensorFlow, PyTorch, Azure ML, SageMaker, etc.). Experience with governance frameworks, data privacy, and MLOps. Excellent communication and stakeholder management skills. Demonstrated ability to lead and inspire technical teams. Preferred Qualifications Experience in AI / GenAI usecase delivery , model interpretability, and regulatory compliance. Prior experience leading enterprise data modernization or AI transformation programs. Certifications in cloud data architecture or AI (e.g., Azure Data Engineer/Architect, AWS Certified Machine Learning). Why Join Us? Be part of a purpose-driven organization that’s shaping the future of mobility. Work on cutting-edge technologies and global projects. Thrive in a collaborative, diverse, and inclusive environment. Access world-class infrastructure and learning opportunities. Equal Opportunity Statement: At MBRDI, we are committed to diversity and inclusion. We welcome applications from all qualified individuals, regardless of gender, background, or ability. Mercedes-Benz Research and Development India Private Limited", "summaryDescription" : "T6_Chief Data and AI Architect at MBRDI. Skills: Data Architecture, AI, ML, Data Engineering. Design scalable data architectures. Oversee data ingestion", "createdAt" : "2026-06-14T08:27:53.793", "lastUpdated" : "2026-06-15T10:23:16.352", "ingestTimestamp" : "2026-06-14T08:27:53.793", "mongoId" : "69ce5e3b9bc74574cb677aec", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data modeling", "Data ingestion", "Data integration", "Metadata management", "Data lineage", "Data quality", "Model lifecycle management", "Model versioning", "Model monitoring", "Risk assessment", "Data Architecture", "AI", "ML", "Data Engineering", "Solution design", "Stakeholder management", "Team leadership", "Thought leadership", "Knowledge sharing", "Technical excellence", "Data lakehouse", "Streaming data", "Unstructured data", "Structured data", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "Responsible AI", "Ethical AI", "Model interpretability", "GenAI", "Azure Data Engineer", "Azure Architect", "AWS Certified Machine Learning", "Dbt Cloud", "Fivetran", "Airflow" ], "skillCount" : 41, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Automotive", "llmIndustryConfidence" : 0.95 }, { "id" : "6a307f57f292fd229c058281", "title" : "Senior Data and Analytics Engineer", "company" : "Velir", "salary" : { "min" : 160000.0, "max" : 175000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Remote", "locations" : [ "Remote" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T10:32:01.810", "fingerprint" : "94ede4f511c38a9621a1a064142cdbb189de1e740bcae1d22083fe7aee1c9284", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/velir/jobs/5262333008", "externalId" : "5262333008", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "SQL, Python, Spark, Dbt, Snowflake, BigQuery, Databricks, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow", "professionalSkills" : [ "Data engineering", "Data modeling", "ETL development", "Data warehousing", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Machine learning", "AI development" ], "hardSkillsList" : [ "Data pipeline development", "Database management", "Cloud data platforms", "Machine learning models", "Statistical analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Data pipeline development", "level" : "intermediate" }, { "name" : "Database management", "level" : "intermediate" }, { "name" : "Cloud data platforms", "level" : "intermediate" }, { "name" : "Machine learning models", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data engineering, Machine learning, Business intelligence, Analytics engineering", "majorSkillsList" : [ "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering" ], "coreResponsibilities" : "Design data pipelines, Build data models, Develop ETL processes, Implement data warehousing solutions, Create business intelligence dashboards, Engineer analytics solutions, Develop and deploy machine learning models, Perform quantitative analysis, Conduct A/B testing, Apply causal inference techniques, Optimize data infrastructure, Ensure data quality and integrity, Collaborate with stakeholders", "teamCollaboration" : "Cross-functional teams; Data science teams; Engineering teams; Product teams; Business stakeholders", "domainKnowledge" : "Cloud data stacks; ML frameworks; BI platforms; Statistical methods", "domainList" : [ "cloud-data-stacks", "ml-frameworks", "bi-platforms", "statistical-methods" ], "domainSpecificKnowledge" : [ "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods" ], "toolProficiency" : [ "Dbt Cloud", "MLflow", "Snowflake", "BigQuery", "Databricks", "AWS SageMaker", "GCP Vertex AI", "Azure ML Studio" ], "qualificationsBasic" : "5+ years of experience in data engineering, Proficiency in SQL, Experience with Python", "qualificationsPreferred" : "Master's degree preferred, Experience with dbt Cloud, Experience with MLflow, Experience with Databricks, Experience with Snowflake, Experience with BigQuery, Experience with AWS SageMaker, Experience with GCP Vertex AI, Experience with Azure ML Studio, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Velir is an established mid-sized agency with a top-tier portfolio of clients, ranging from the world’s largest non-profits to Fortune 500 brands. As of 2023, Velir acquired Brooklyn Data Company, a premier data and analytics consultancy focused on leadership, process improvement, implementation, and advanced analytics. At Velir, we believe people are our greatest asset. Our culture is built on a foundation of trust, collaboration, and continued improvement. We strive for excellence in everything we do, embracing challenges as opportunities for growth. Our success is driven by a shared passion for making a positive impact on our customers, our communities and each other. We are a remote first company that offers competitive pay and excellent benefits. Overview The Senior Data & Analytics Engineer will play a crucial role in helping our client organizations transform raw data into reliable, well-modeled assets that drive business decisions. This hybrid role bridges data engineering and analytics engineering — combining the infrastructure-building strengths of a data engineer with the transformation, modeling, and semantic layer expertise of an analytics engineer. Core responsibilities include Data Architecture Design, Data Modeling, ELT/ETL Development, Data Quality Assurance, and Scalability Optimization, with a strong emphasis on Databricks as the primary platform. Because our clients are mostly US-based organizations, we look for the ability to communicate with professional proficiency in English, verbally and in writing. Responsibilities Data & Analytics Engineering Expertise: You are responsible for building and maintaining the infrastructure and transformation layers that support the storing, movement, and modeling of data — enabling analysts, AI agents, and business stakeholders to confidently consume, interpret and take action. You will operate across both the data engineering and analytics engineering layers of the data stack, owning pipeline development and maintenance, as well as designing and building the resultant data models. Design, build, and maintain scalable data pipelines and ELT workflows, with Databricks as the primary platform Develop and maintain dbt models that are well-documented, tested, and structured for long-term maintainability Own data modeling decisions and methodology — defining entities, relationships, and grain — in collaboration with analytics and business stakeholders Consistently seek out and deliver on engagement-level vision, tasks, and problems Regularly delivers meaningful improvements to clients' data infrastructure and analytical capabilities Autonomous in approach and provides technical guidance to less experienced engineers Cross-Team Collaboration: You are responsible for collaborating with peers and other functional departments to develop and implement data strategies that support engagement goals and client needs. Collaborate with other data engineers and analytics engineers, data analysts, and clients on end-to-end data requirements Partner with clients and functional managers to plan for data engineering and modeling needs for product or feature launches Create processes and/or documentation templates that help cross-functional teams solve common data problems Drive data solution improvements that impact the client experience or empower internal stakeholders to do their jobs effectively Take initiative to identify, communicate, and solve important problems, coordinating with others on cross-cutting technical issues Project Delivery: You are responsible for ensuring that data engineering and analytics engineering projects are delivered on time, within scope, and within budget. Architect and design data systems and transformation layers using patterns that allow for iterative delivery and future scaling Proactively identify and address technical debt with careful evaluation of development cost Optimize for predictability and a regular cadence of deliverables Keep reliability, maintainability, and scalability of client systems top of mind Ability to identify and prioritize unowned or unglamorous work that enables the broader team to move faster Skills & Qualifications Proven experience as a Data Engineer, Analytics Engineer, or in a hybrid or generalist role, with a focus on designing and developing data pipelines and transformation layers Strong programming skills in Python and SQL Hands-on, deep expertise with Databricks — including Delta Lake, Unity Catalog, and Databricks workflows Strong proficiency with dbt for data transformation, testing, and documentation Demonstrated experience in data modeling — including dimensional modeling, entity-relationship design, and semantic layer development Deep knowledge of data warehousing and ELT/ETL processes Familiarity with data integration and orchestration platforms (e.g., Fivetran, Apache Airflow, Azure Data Factory) Experience with cloud platforms such as AWS, Azure, or Google Cloud Experience with other cloud data warehouses such as Snowflake or Motherduck is a plus Experience with streaming solutions such as Spark Streaming or Kafka is desirable but not required Familiarity with MLOps techniques and platforms is a plus but not required Strong analytical and problem-solving skills Excellent communication and collaboration skills Familiarity with leveraging coding assistants such as Claude Code, CoPilot, and/or Codex is a plus Physical Requirements Frequent sitting at a desk performing work on a computer Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions Compensation Range: $160,000 - 175,000 annually Please note that compensation packages are finalized after the interview process is concluded. We use a competency-based approach to base pay, which means it is based on the competencies and skills demonstrated for this role. Core Company Values Take the Long View - Ensure the company is built to last Be Courageous - Make the right decisions even when they aren't the easiest decisions Be Genuine - Bring honesty and authenticity to all that you do Work with Focus + Passion - Display purpose and pride in your work and never stop learning As an equal opportunity employer, we are firmly committing to diversity, equity, and inclusion in our hiring efforts. We recognize that we need team members from all backgrounds and experiences to successfully shape a positive employee experience as well as deliver our product and service solutions. To that end, we actively seek candidates who can bring diverse experiences and backgrounds to our team. We know that complex factors and systemic bias can get in the way of us meeting strong candidates, so please don't hesitate to apply even if you're not 100% sure. At this time, Velir does not sponsor candidates and unfortunately cannot accept those on OPT or CPT.", "summaryDescription" : "Senior Data and Analytics Engineer at Velir. Skills: Data engineering, Machine learning, Business intelligence, Analytics engineering. Design data pipelines. Build data models", "postedDate" : "2026-06-16T01:18:38.223", "createdAt" : "2026-06-16T01:18:38.223", "lastUpdated" : "2026-06-16T10:32:01.810", "ingestTimestamp" : "2026-06-16T01:18:38.223", "mongoId" : "6a307f57f292fd229c058281", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 160000, "salaryAnnualMax" : 175000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipeline development", "Database management", "Cloud data platforms", "Machine learning models", "Statistical analysis", "A/B testing", "Causal inference", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Data modeling", "ETL development", "Data warehousing", "Quantitative analysis", "AI development", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Dbt Cloud", "MLflow", "Snowflake", "BigQuery", "Databricks", "AWS SageMaker", "GCP Vertex AI", "Azure ML Studio" ], "skillCount" : 32, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a306647f292fd229cfafc8d", "title" : "Lead Product Manager, Data and AI", "company" : "Lyra Health", "industry" : "Product", "salary" : { "min" : 161000.0, "max" : 221500.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "United States", "locations" : [ "United States" ], "timestamp" : "2026-06-16T11:46:32.032", "fingerprint" : "7be737cc8ee8a6035793f5d2e69d5f06381cd02b4aff658c15d77ee3e54d1515", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/lyrahealth/e3d731e8-eea0-4ae4-bd9a-5624b91ca129/apply", "externalId" : "e3d731e8-eea0-4ae4-bd9a-5624b91ca129", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "coreResponsibilities" : "Develop product strategy, Define product roadmap, Write user stories, Collaborate with cross-functional teams", "teamCollaboration" : "Cross-functional teams", "remoteFriendly" : true, "rawDescription" : "## Description About Lyra Health Lyra Health is a leading provider of evidence-based mental health care, serving more than 20 million people globally in partnership with employers and more than 100 million through health plan and partner relationships. The company has delivered more than 15 million sessions of mental health care, published more than 35 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness, and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions. ## Responsibilities Product Vision & Strategy: Define and champion a compelling multi-year product vision and roadmap for data and AI platforms, aligning technical milestones with Lyra's business growth, revenue objectives, and clinical goals. GenAI & Modern Lifecycle Management: Drive high-impact opportunities leveraging generative AI, Large Language Models (LLMs), agentic AI, and advanced analytics, managing the entire lifecycle from ideation and rapid experimentation to scalable production deployment. Cross-Functional Leadership: Collaborate extensively across complex matrixed stakeholder groups—including Product, Design, Engineering, Clinical Quality, and GTM teams—to embed smart AI capabilities directly into core member experiences and operations. Responsible AI & Governance: Partner closely with Legal, Privacy, and Clinical leadership to maintain rigorous responsible AI practices Impact Metrics & Optimization: Design robust measurement and experimentation frameworks (such as online controlled A/B testing) to track model effectiveness, quantify business outcomes, and evaluate trade-offs between tactical execution and long-term research. Technical Team Collaboration: Translate unstructured business pain points into crisp, detailed product requirements, acting as a translator between highly technical data disciplines and non-technical business leaders. Mentorship & Culture: Lead by example, mentoring junior team members, sharing technical product management best practices, and actively fostering a highly rigorous, data-driven culture across the product organization. ## Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related highly quantitative field. Product Experience: 8+ years (Lead PM) of progressive product management experience within successful enterprise SaaS, cloud-based software, or health tech organizations, with a proven history of launching large-scale products with complex dependencies. Data & AI Expertise: 3+ years of direct experience shipping machine learning and data-driven products at scale. Deep understanding of modern machine learning algorithms, deep learning techniques, generative AI use cases, and the infrastructure needed to deploy LLMs contextually. Communication Skills: Exceptional written and verbal communication, narrative storytelling, and presentation skills; masterful ability to communicate complex algorithmic systems and technical trade-offs to non-technical executive teams and demanding corporate customer audiences. Strategic Execution: Proven capacity to methodically unpack ambiguity, handle competing objectives, establish clear product boundaries, and maintain a calm, execution-oriented mindset in a fast-paced, high-velocity environment. Healthcare Alignment (Nice-to-Have): Prior experience navigating a highly regulated industry (Healthcare Tech, FinTech) with an innate respect for data ethics, privacy constraints, and patient clinical quality. ## Additional Information \"We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law. By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra. We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR. Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives. If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form. This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice.\"", "summaryDescription" : "Lead Product Manager, Data and AI at Lyra Health. Develop product strategy. Define product roadmap", "postedDate" : "2026-06-15T02:55:35.385", "createdAt" : "2026-06-15T02:55:35.385", "lastUpdated" : "2026-06-16T11:46:32.032", "ingestTimestamp" : "2026-06-16T03:24:16.833", "mongoId" : "6a306647f292fd229cfafc8d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 161000, "salaryAnnualMax" : 221500, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2d024e74d8ee00a0abbc9d", "title" : "Data and AI Marketing Intern", "salary" : { "min" : 45000.0, "max" : 65000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data and AI Marketing Intern in Alexandria, United States, adjusted for the technology industry." }, "location" : "Alexandria, VA", "locations" : [ "Alexandria, VA" ], "timestamp" : "2026-06-16T06:12:07.063", "fingerprint" : "4f4c4efce6ad0b5bd7f08cf27db19dffaac43726855640ef3a2b30d36e1a76f1", "source" : "jazzhr", "language" : "en", "externalId" : "5wjRGUZ0z4", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Alexandria", "state" : "Virginia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "38.8051095,-77.0470229" } ], "locationText" : "Alexandria, Virginia, United States", "employmentType" : "INTERNSHIP", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "remoteFriendly" : false, "summaryDescription" : "Data and AI Marketing Intern", "createdAt" : "2026-06-14T19:12:31.506", "lastUpdated" : "2026-06-16T06:12:07.063", "ingestTimestamp" : "2026-06-14T19:12:31.506", "mongoId" : "6a2d024e74d8ee00a0abbc9d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 45000, "salaryAnnualMax" : 65000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "marketing", "jobSubcategory" : "growth", "seniorityLevel" : "Entry", "dataQualityScore" : 0.5555556, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306e31f292fd229cfdd346", "title" : "Customer Engineering Director", "company" : "UiPath", "industry" : "Review", "salary" : { "min" : 1500000.0, "max" : 2500000.0, "currency" : "HKD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Director of Customer Engineering in Hong Kong's SaaS industry, adjusted for seniority and company size." }, "location" : "Hong Kong", "locations" : [ "Hong Kong", "Remote-Taipei", "Shanghai", "Beijing" ], "timestamp" : "2026-06-16T12:15:24.109", "fingerprint" : "77d31eeaf43fb02e9441cc4be6ae2975e199204cd0765c841393b2f3709e34b3", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/uipath/26d701c2-3532-4b39-bb17-26d85caf0996/application", "externalId" : "26d701c2-3532-4b39-bb17-26d85caf0996", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hong Kong", "country" : "Hong Kong", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "22.2818333,114.1582831" } ], "locationText" : "Hong Kong, Hong Kong", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "Automation, AI, SaaS, Cloud platforms", "professionalSkills" : [ "Solution design", "Pipeline acceleration", "Go-to-market strategy", "Project governance" ], "hardSkillsList" : [ "Technical advisory", "Solution engineering", "Platform guidance", "Adoption expertise", "Technical storytelling", "Executive communication", "Customer discovery", "Competitive positioning", "Advisory conversations", "Technical recommendations", "Customer business outcomes", "Platform maturity", "Customer patterns", "Adoption blockers", "Competitive insights", "Product feedback", "Reusable playbooks", "Demo assets", "POC approaches", "Adoption frameworks", "Technical best practices", "Account planning", "Business reviews", "Technical positioning", "Go-to-market narratives", "Resource coordination", "Milestone tracking", "Stakeholder management", "Implementation", "Go-live" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Technical advisory", "level" : "intermediate" }, { "name" : "Solution engineering", "level" : "intermediate" }, { "name" : "Platform guidance", "level" : "intermediate" }, { "name" : "Adoption expertise", "level" : "intermediate" }, { "name" : "Technical storytelling", "level" : "intermediate" }, { "name" : "Executive communication", "level" : "intermediate" }, { "name" : "Customer discovery", "level" : "intermediate" }, { "name" : "Competitive positioning", "level" : "intermediate" }, { "name" : "Advisory conversations", "level" : "intermediate" }, { "name" : "Technical recommendations", "level" : "intermediate" }, { "name" : "Customer business outcomes", "level" : "intermediate" }, { "name" : "Platform maturity", "level" : "intermediate" }, { "name" : "Customer patterns", "level" : "intermediate" }, { "name" : "Adoption blockers", "level" : "intermediate" }, { "name" : "Competitive insights", "level" : "intermediate" }, { "name" : "Product feedback", "level" : "intermediate" }, { "name" : "Reusable playbooks", "level" : "intermediate" }, { "name" : "Demo assets", "level" : "intermediate" }, { "name" : "POC approaches", "level" : "intermediate" }, { "name" : "Adoption frameworks", "level" : "intermediate" }, { "name" : "Technical best practices", "level" : "intermediate" }, { "name" : "Account planning", "level" : "intermediate" }, { "name" : "Business reviews", "level" : "intermediate" }, { "name" : "Technical positioning", "level" : "intermediate" }, { "name" : "Go-to-market narratives", "level" : "intermediate" }, { "name" : "Resource coordination", "level" : "intermediate" }, { "name" : "Milestone tracking", "level" : "intermediate" }, { "name" : "Stakeholder management", "level" : "intermediate" }, { "name" : "Implementation", "level" : "intermediate" }, { "name" : "Go-live", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Customer Engineering, Professional Services, Go-to-market strategy", "majorSkillsList" : [ "Customer Engineering", "Professional Services", "Go-to-market strategy" ], "coreResponsibilities" : "Lead customer-facing technical team, Guide team's execution, Partner with GTM leadership, Prioritize customer engagements, Prioritize technical pursuits, Prioritize adoption opportunities, Ensure team focus on high-impact accounts, Ensure team focus on high-impact opportunities, Ensure team focus on customer outcomes, Review quality of technical strategies, Review quality of POCs, Review quality of adoption plans, Review quality of customer advisory engagements, Coach team members, Support strategic customer engagements, Build team capability, Hire team members, Onboard team members, Enable team members, Manage team performance, Develop team careers, Connect technical recommendations, Monitor regional customer patterns, Monitor adoption blockers, Monitor competitive insights, Monitor product feedback, Share feedback with internal teams, Promote use of playbooks, Promote use of demo assets, Promote use of POC approaches, Promote use of adoption frameworks, Promote use of technical best practices, Represent regional technical perspective, Collaborate with GTM leadership, Identify potential services opportunities, Understand customer requirements, Draft SOWs, Oversee Professional Services delivery, Ensure on-time delivery, Ensure on-budget delivery, Act as senior delivery point of contact, Manage escalations, Manage milestone reviews, Manage customer satisfaction, Define delivery standards, Maintain delivery standards, Define project governance frameworks, Maintain project governance frameworks", "teamCollaboration" : "Partnering with GTM leadership; Partnering with sales leadership; Working across pre-sales; Working across delivery; Working across post-sales; Collaborate with GTM leadership; Work with regional sales", "projectManagementSkills" : [ "Project governance" ], "domainKnowledge" : "Enterprise software; Automation; AI; SaaS; Cloud platforms; Architecture; Integrations; Security; Deployment considerations; Professional Services; Go-to-market strategy", "domainList" : [ "enterprise-software", "automation", "ai", "saas", "cloud-platforms", "architecture", "integrations", "security", "deployment-considerations", "professional-services", "go-to-market-strategy" ], "domainSpecificKnowledge" : [ "Enterprise software", "Automation", "AI", "SaaS", "Cloud platforms", "Architecture", "Integrations", "Security", "Deployment considerations", "Professional Services", "Go-to-market strategy" ], "toolProficiency" : [ "UiPath" ], "communicationSkills" : "Executive communication; Customer discovery; Competitive positioning; Advisory conversations; Technical storytelling; Executive presence", "outcomesObjectives" : "Improve technical win rates; Improve adoption outcomes; Improve expansion potential; Improve long-term customer value", "qualificationsBasic" : "Experience leading customer-facing technical teams, Understanding of enterprise software, Understanding of automation, Understanding of AI, Understanding of SaaS/cloud platforms, Understanding of architecture, Understanding of integrations, Understanding of security, Understanding of deployment considerations, Experience across pre-sales customer motions, Experience across post-sales customer motions, Proven ability to build technical field function, Commercial awareness, Credibility with senior technical stakeholders, Credibility with senior business stakeholders, Ability to coach teams on demos, Ability to coach teams on POCs, Ability to coach teams on competitive positioning, Ability to coach teams on technical storytelling, Ability to coach teams on solution design, Ability to coach teams on customer advisory conversations, Judgment in complex customer situations, Judgment in ambiguous customer situations, Excellent communication skills, Excellent executive presence, Excellent stakeholder management skills, Fluency in Mandarin, Fluency in English, Experience overseeing Professional Services engagements, Experience delivering Professional Services engagements", "qualificationsPreferred" : "Experience with Kubernetes a plus, Experience with container orchestration platforms a plus", "workSiteFlexibility" : "Flexible", "rawDescription" : "LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? YOUR MISSION We are looking for an experienced Director of Customer Engineering to lead our customer-facing technical team in Greater China, covering Mainland China, Taiwan, and Hong Kong. You will guide a team of consultants who operate across the full customer lifecycle - from first technical conversation to successful platform adoption. The team brings together strong technical advisory, solution engineering, platform guidance, and adoption expertise to help customers evaluate, implement, and expand their use of UiPath. You will be responsible for the performance, prioritization, coaching, and execution quality of the team. Beyond leading the core Customer Engineering function, you will play an active role in shaping regional services go-to-market strategy — partnering with GTM and sales leadership on field plays, solution positioning, and pipeline acceleration. You will also carry accountability for the delivery quality of Professional Services engagements in the region, ensuring customers move from contract to value with speed and confidence. Working across pre-sales, delivery, and post-sales motions, you will help the region improve technical win rates, adoption outcomes, expansion potential, and long-term customer value realization. WHAT YOU'LL DO AT UIPATH • Lead, coach, and develop your team across Mainland China, Taiwan, and Hong Kong • Guide the team's execution across demos, technical discovery, POCs, competitive positioning, solution design advisory, platform setup recommendations, and post-sales technical guidance • Partner with GTM leadership to prioritize customer engagements, technical pursuits, and adoption opportunities • Ensure the team is focused on the highest-impact accounts, opportunities, and customer outcomes • Review and improve the quality of technical account strategies, POCs, adoption plans, and customer advisory engagements • Coach team members on technical storytelling, executive communication, customer discovery, competitive positioning, and advisory conversations. • Support complex or strategic customer engagements where senior technical leadership is required • Build team capability through hiring, onboarding, enablement, performance management, and career development • Help the team connect technical recommendations with customer business outcomes, adoption milestones, and long-term platform maturity • Monitor regional customer patterns, adoption blockers, competitive insights, and product feedback, and share them with relevant internal teams • Promote consistent use of reusable playbooks, demo assets, POC approaches, adoption frameworks, and technical best practices • Represent the regional technical perspective in account planning, business reviews, and leadership discussions • Collaborate with GTM leadership on regional go-to-market strategy, work with regional sales for identifying potential services opportunities, understand customer requirements and help draft solutions; draft SOWs • Oversee scoped Professional Services delivery engagements for strategic accounts in the region, ensuring on-time, on-budget outcomes; act as the senior delivery point of contact for escalations, milestone reviews, and customer satisfaction during implementation phases • Define and maintain delivery standards, project governance frameworks, to ensure consistency and quality across Professional Services engagements in the region. WHAT YOU'LL BRING TO THE TEAM • Experience leading customer-facing technical teams such as Sales Engineering, Solution Consulting, Technical Account Management, Customer Engineering, or Technical Consulting • Strong understanding of enterprise software, automation, AI, SaaS/cloud platforms, architecture, integrations, security, and deployment considerations • Experience across both pre-sales and post-sales customer motions • Proven ability to build or evolve a technical field function, including role definition, engagement models, KPIs, and enablement • Commercial awareness, with the ability to support pipeline progression, technical win strategies, adoption, expansion, and retention • Credibility with senior technical and business stakeholders, including executives, architects, automation leaders, and transformation owners • Ability to coach teams on demos, POCs, competitive positioning, technical storytelling, solution design, and customer advisory conversations • Strong judgment in complex or ambiguous customer situations • Excellent communication, executive presence, and stakeholder management skills • Fluency in Mandarin and English, written and spoken • Familiarity with GTM motions, solution plays, partner and pipeline generation strategies; ability to translate technical positioning into compelling go-to-market narratives for services • Experience overseeing or directly delivering Professional Services engagements, including project governance, resource coordination, milestone tracking, and customer stakeholder management through implementation and go-live. Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.", "summaryDescription" : "Customer Engineering Director at UiPath. Skills: Customer Engineering, Professional Services, Go-to-market strategy. Lead customer-facing technical team. Guide team's execution", "createdAt" : "2026-06-16T00:27:58.404", "lastUpdated" : "2026-06-16T12:15:24.109", "ingestTimestamp" : "2026-06-16T00:27:58.404", "mongoId" : "6a306e31f292fd229cfdd346", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Technical advisory", "Solution engineering", "Platform guidance", "Adoption expertise", "Technical storytelling", "Executive communication", "Customer discovery", "Competitive positioning", "Advisory conversations", "Technical recommendations", "Customer business outcomes", "Platform maturity", "Customer patterns", "Adoption blockers", "Competitive insights", "Product feedback", "Reusable playbooks", "Demo assets", "POC approaches", "Adoption frameworks", "Technical best practices", "Account planning", "Business reviews", "Technical positioning", "Go-to-market narratives", "Resource coordination", "Milestone tracking", "Stakeholder management", "Implementation", "Go-live", "Leadership", "Customer Engineering", "Professional Services", "Go-to-market strategy", "Solution design", "Pipeline acceleration", "Project governance", "Enterprise software", "Automation", "AI", "SaaS", "Cloud platforms", "Architecture", "Integrations", "Security", "Deployment considerations", "UiPath" ], "skillCount" : 47, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306e31f292fd229cfdd347", "title" : "Customer Engineering Director", "company" : "UiPath", "industry" : "Review", "salary" : { "min" : 1.5E8, "max" : 2.2E8, "currency" : "KRW", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Director of Customer Engineering in Seoul, South Korea, adjusted for the SaaS industry and company size." }, "location" : "Seoul", "locations" : [ "Seoul" ], "timestamp" : "2026-06-16T14:00:53.684", "fingerprint" : "6cad9e585d3fe6012ef2dec68846105d3ee58e9ab478e84816499a8892eeef2c", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/uipath/7557cd94-4b59-4624-aa2d-7bdeaacb9474/application", "externalId" : "7557cd94-4b59-4624-aa2d-7bdeaacb9474", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seoul", "country" : "South Korea", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "37.5666791,126.9782914" } ], "locationText" : "Seoul, South Korea", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "Automation, AI, SaaS, Cloud platforms", "professionalSkills" : [ "Solution design", "Customer advisory", "Go-to-market strategy", "Pipeline acceleration", "Delivery quality", "Technical win rates", "Adoption outcomes", "Expansion potential", "Customer value realization", "Technical pursuits", "Adoption plans", "Account strategies", "Technical storytelling", "Executive communication", "Customer discovery", "Advisory conversations", "Account planning", "Business reviews", "Stakeholder management", "Pipeline generation", "Go-to-market narratives", "Project governance", "Resource coordination", "Milestone tracking" ], "hardSkillsList" : [ "Platform setup", "Technical recommendations", "Product feedback", "Playbooks", "Demo assets", "POC approaches", "Adoption frameworks", "Technical best practices", "SOW drafting", "On-time delivery", "On-budget delivery", "Milestone reviews", "Customer satisfaction", "Delivery standards", "Project governance frameworks" ], "softSkillsList" : [ "Leadership", "Judgment" ], "hardSkills" : [ { "name" : "Platform setup", "level" : "intermediate" }, { "name" : "Technical recommendations", "level" : "intermediate" }, { "name" : "Product feedback", "level" : "intermediate" }, { "name" : "Playbooks", "level" : "intermediate" }, { "name" : "Demo assets", "level" : "intermediate" }, { "name" : "POC approaches", "level" : "intermediate" }, { "name" : "Adoption frameworks", "level" : "intermediate" }, { "name" : "Technical best practices", "level" : "intermediate" }, { "name" : "SOW drafting", "level" : "intermediate" }, { "name" : "On-time delivery", "level" : "intermediate" }, { "name" : "On-budget delivery", "level" : "intermediate" }, { "name" : "Milestone reviews", "level" : "intermediate" }, { "name" : "Customer satisfaction", "level" : "intermediate" }, { "name" : "Delivery standards", "level" : "intermediate" }, { "name" : "Project governance frameworks", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Judgment" } ], "majorSkills" : "Customer Engineering, Solution Engineering, Platform Guidance, Adoption Expertise", "majorSkillsList" : [ "Customer Engineering", "Solution Engineering", "Platform Guidance", "Adoption Expertise" ], "coreResponsibilities" : "Lead team, Coach team, Develop team, Guide team execution, Partner with GTM leadership, Prioritize customer engagements, Prioritize technical pursuits, Prioritize adoption opportunities, Ensure team focus on high-impact accounts, Ensure team focus on high-impact opportunities, Ensure team focus on high-impact customer outcomes, Review quality of technical account strategies, Review quality of POCs, Review quality of adoption plans, Review quality of customer advisory engagements, Coach team members on technical storytelling, Coach team members on executive communication, Coach team members on customer discovery, Coach team members on competitive positioning, Coach team members on advisory conversations, Support complex customer engagements, Support strategic customer engagements, Build team capability through hiring, Build team capability through onboarding, Build team capability through enablement, Build team capability through performance management, Build team capability through career development, Help team connect technical recommendations with customer business, Help team connect technical recommendations with adoption milestones, Help team connect technical recommendations with long-term platform, Monitor regional customer patterns, Monitor adoption blockers, Monitor competitive insights, Monitor product feedback, Share insights with internal teams, Promote consistent use of reusable playbooks, Promote consistent use of reusable demo assets, Promote consistent use of reusable POC approaches, Promote consistent use of reusable adoption frameworks, Promote consistent use of reusable technical best practices, Represent regional technical perspective in account planning, Represent regional technical perspective in business reviews, Represent regional technical perspective in leadership discussions, Collaborate with GTM leadership on regional go-to-market strategy, Work with regional sales for identifying potential services, Understand customer requirements, Help draft SOWs, Oversee scoped Professional Services delivery engagements, Ensure on-time delivery of engagements, Ensure on-budget delivery of engagements, Act as senior delivery point of contact for, Act as senior delivery point of contact for, Act as senior delivery point of contact for, Define delivery standards, Maintain delivery standards, Define project governance frameworks, Maintain project governance frameworks", "teamCollaboration" : "Partner with GTM leadership; Work with regional sales; Collaborate with GTM leadership; Cross-functional teams", "projectManagementSkills" : [ "Project governance", "Resource coordination", "Milestone tracking" ], "domainKnowledge" : "Enterprise software; Automation; AI; SaaS; Cloud platforms; Architecture; Integrations; Security; Deployment considerations", "domainList" : [ "enterprise-software", "automation", "ai", "saas", "cloud-platforms", "architecture", "integrations", "security", "deployment-considerations" ], "domainSpecificKnowledge" : [ "Enterprise software", "Automation", "AI", "SaaS", "Cloud platforms", "Architecture", "Integrations", "Security", "Deployment considerations" ], "toolProficiency" : [ "UiPath" ], "communicationSkills" : "Executive communication; Technical storytelling; Customer advisory conversations; Stakeholder management", "outcomesObjectives" : "Improve technical win rates; Improve adoption outcomes; Improve expansion potential; Improve long-term customer value realization; Ensure on-time delivery; Ensure on-budget delivery; Ensure customer satisfaction", "qualificationsBasic" : "Experience leading customer-facing technical teams, Understanding of enterprise software, Understanding of automation, Understanding of AI, Understanding of SaaS/cloud platforms, Understanding of architecture, Understanding of integrations, Understanding of security, Understanding of deployment considerations, Experience across pre-sales motions, Experience across post-sales motions, Ability to build or evolve technical field function, Commercial awareness, Credibility with senior technical stakeholders, Credibility with senior business stakeholders, Ability to coach teams on demos, Ability to coach teams on POCs, Ability to coach teams on competitive positioning, Ability to coach teams on technical storytelling, Ability to coach teams on solution design, Ability to coach teams on customer advisory conversations, Judgment in complex customer situations, Judgment in ambiguous customer situations, Fluency in Korean, Fluency in English, Experience overseeing Professional Services engagements, Experience delivering Professional Services engagements", "qualificationsPreferred" : "Experience with Kubernetes, Experience with container orchestration platforms", "workSiteFlexibility" : "Flexible", "rawDescription" : "LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? YOUR MISSION We are looking for an experienced Director of Customer Engineering to lead our customer-facing technical team in Korea. You will guide a team of consultants who operate across the full customer lifecycle - from first technical conversation to successful platform adoption. The team brings together strong technical advisory, solution engineering, platform guidance, and adoption expertise to help customers evaluate, implement, and expand their use of UiPath. You will be responsible for the performance, prioritization, coaching, and execution quality of the team. Beyond leading the core Customer Engineering function, you will play an active role in shaping regional services go-to-market strategy — partnering with GTM and sales leadership on field plays, solution positioning, and pipeline acceleration. You will also carry accountability for the delivery quality of Professional Services engagements in the region, ensuring customers move from contract to value with speed and confidence. Working across pre-sales, delivery, and post-sales motions, you will help the region improve technical win rates, adoption outcomes, expansion potential, and long-term customer value realization. WHAT YOU'LL DO AT UIPATH • Lead, coach, and develop your team • Guide the team's execution across demos, technical discovery, POCs, competitive positioning, solution design advisory, platform setup recommendations, and post-sales technical guidance • Partner with GTM leadership to prioritize customer engagements, technical pursuits, and adoption opportunities • Ensure the team is focused on the highest-impact accounts, opportunities, and customer outcomes • Review and improve the quality of technical account strategies, POCs, adoption plans, and customer advisory engagements • Coach team members on technical storytelling, executive communication, customer discovery, competitive positioning, and advisory conversations. • Support complex or strategic customer engagements where senior technical leadership is required • Build team capability through hiring, onboarding, enablement, performance management, and career development • Help the team connect technical recommendations with customer business outcomes, adoption milestones, and long-term platform maturity • Monitor regional customer patterns, adoption blockers, competitive insights, and product feedback, and share them with relevant internal teams • Promote consistent use of reusable playbooks, demo assets, POC approaches, adoption frameworks, and technical best practices • Represent the regional technical perspective in account planning, business reviews, and leadership discussions • Collaborate with GTM leadership on regional go-to-market strategy, work with regional sales for identifying potential services opportunities, understand customer requirements and help draft solutions; draft SOWs • Oversee scoped Professional Services delivery engagements for strategic accounts in the region, ensuring on-time, on-budget outcomes; act as the senior delivery point of contact for escalations, milestone reviews, and customer satisfaction during implementation phases • Define and maintain delivery standards, project governance frameworks, to ensure consistency and quality across Professional Services engagements in the region. WHAT YOU'LL BRING TO THE TEAM • Experience leading customer-facing technical teams such as Sales Engineering, Solution Consulting, Technical Account Management, Customer Engineering, or Technical Consulting • Strong understanding of enterprise software, automation, AI, SaaS/cloud platforms, architecture, integrations, security, and deployment considerations • Experience across both pre-sales and post-sales customer motions • Proven ability to build or evolve a technical field function, including role definition, engagement models, KPIs, and enablement • Commercial awareness, with the ability to support pipeline progression, technical win strategies, adoption, expansion, and retention • Credibility with senior technical and business stakeholders, including executives, architects, automation leaders, and transformation owners • Ability to coach teams on demos, POCs, competitive positioning, technical storytelling, solution design, and customer advisory conversations • Strong judgment in complex or ambiguous customer situations • Excellent communication, executive presence, and stakeholder management skills • Fluency in Korean and English, written and spoken • Familiarity with GTM motions, solution plays, partner and pipeline generation strategies; ability to translate technical positioning into compelling go-to-market narratives for services • Experience overseeing or directly delivering Professional Services engagements, including project governance, resource coordination, milestone tracking, and customer stakeholder management through implementation and go-live. Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.", "summaryDescription" : "Customer Engineering Director at UiPath. Skills: Customer Engineering, Solution Engineering, Platform Guidance, Adoption Expertise. Lead team. Coach team", "createdAt" : "2026-06-16T00:26:59.357", "lastUpdated" : "2026-06-16T14:00:53.684", "ingestTimestamp" : "2026-06-16T00:26:59.357", "mongoId" : "6a306e31f292fd229cfdd347", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Platform setup", "Technical recommendations", "Product feedback", "Playbooks", "Demo assets", "POC approaches", "Adoption frameworks", "Technical best practices", "SOW drafting", "On-time delivery", "On-budget delivery", "Milestone reviews", "Customer satisfaction", "Delivery standards", "Project governance frameworks", "Leadership", "Judgment", "Customer Engineering", "Solution Engineering", "Platform Guidance", "Adoption Expertise", "Solution design", "Customer advisory", "Go-to-market strategy", "Pipeline acceleration", "Delivery quality", "Technical win rates", "Adoption outcomes", "Expansion potential", "Customer value realization", "Technical pursuits", "Adoption plans", "Account strategies", "Technical storytelling", "Executive communication", "Customer discovery", "Advisory conversations", "Account planning", "Business reviews", "Stakeholder management", "Pipeline generation", "Go-to-market narratives", "Project governance", "Resource coordination", "Milestone tracking", "Enterprise software", "Automation", "AI", "SaaS", "Cloud platforms", "Architecture", "Integrations", "Security", "Deployment considerations", "UiPath" ], "skillCount" : 55, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6a8f74d8ee00a090c9ce", "title" : "Sr Director, Data and Application Engineering", "company" : "ABACUS", "industry" : "Technology", "salary" : { "min" : 245000.0, "max" : 375000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data for a Sr Director, Data and Application Engineering in the Technology industry in the United States, adjusted for seniority and remote work." }, "location" : "Remote in US", "locations" : [ "Remote in US" ], "timestamp" : "2026-06-15T21:47:59.306", "fingerprint" : "7470b233e5544201af654abb5b65c275bc32fcf3e35253199982be98ed3b7f16", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://abacustechnology.com/about/careers/current-vacancies/?gh_jid=7726360003", "externalId" : "7726360003", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "AI/ML, Data platform, DevOps, Application Development, CI/CD, Automation tooling, ServiceNow development, ServiceNow configuration, AI-powered tools, AI agents", "professionalSkills" : [ "Strategic leadership", "Execution focus", "Technical strategy", "Stakeholder management", "Organizational design", "Team development", "Cross-functional collaboration", "Executive communication" ], "hardSkillsList" : [ "Metrics definition", "KPI tracking", "Risk reporting", "Outcome reporting", "Governance standards", "Compliance standards", "Security standards" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Metrics definition", "level" : "intermediate" }, { "name" : "KPI tracking", "level" : "intermediate" }, { "name" : "Risk reporting", "level" : "intermediate" }, { "name" : "Outcome reporting", "level" : "intermediate" }, { "name" : "Governance standards", "level" : "intermediate" }, { "name" : "Compliance standards", "level" : "intermediate" }, { "name" : "Security standards", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data Engineering, Application Development, DevOps, AI Development", "majorSkillsList" : [ "Data Engineering", "Application Development", "DevOps", "AI Development" ], "coreResponsibilities" : "Lead technical teams, Drive engineering initiatives, Oversee practice areas, Align teams to goals, Ensure rigorous practices, Ensure velocity, Ensure collaboration, Build enterprise-grade platforms, Build enterprise-grade solutions, Support career development, Define KPIs, Track KPIs, Report progress, Report risks, Report outcomes, Ensure practices meet governance, Ensure practices meet compliance, Ensure practices meet security, Architect enterprise data platform, Resource enterprise data platform, Deliver data platform capabilities, Structure ServiceNow backlog, Prioritize ServiceNow backlog, Progress ServiceNow development, Identify DevOps automation initiatives, Scope DevOps automation initiatives, Deliver DevOps automation efficiency, Own Abacus portal roadmap, Communicate Abacus portal roadmap, Progress Abacus portal development, Deploy AI solutions, Deliver AI business value, Define team charters, Define team goals, Define team delivery metrics, Reflect cross-team collaboration, Reflect consistent delivery", "teamCollaboration" : "Cross-functional teams; Internal stakeholders; Executive leadership; Service delivery team; Across multiple disciplines", "projectManagementSkills" : [ "Roadmap planning", "Prioritization" ], "domainKnowledge" : "Regulated environments; Financial services; Healthcare; Managed Services Provider (MSP); ITSM platforms; Data lakes; Lakehouses; Data mesh architectures", "domainList" : [ "regulated-environments", "financial-services", "healthcare", "managed-services-provider-msp", "itsm-platforms", "data-lakes", "lakehouses", "data-mesh-architectures" ], "domainSpecificKnowledge" : [ "Regulated environments", "Financial services", "Healthcare", "Managed Services Provider (MSP)", "ITSM platforms", "Data lakes", "Lakehouses", "Data mesh architectures" ], "toolProficiency" : [ "ServiceNow" ], "communicationSkills" : "Executive communication; Stakeholder management; Compelling communication", "continuousLearning" : "Online courses", "outcomesObjectives" : "Enterprise data platform foundation architected; Enterprise data platform resourced; Enterprise data platform delivering capabilities; ServiceNow development backlog progressing; DevOps automation delivering efficiency; Abacus portal roadmap progressing; AI solutions deployed; AI solutions delivering value; Teams operate with clear charters; Teams operate with clear goals; Teams operate with clear metrics; Engineering culture reflects collaboration; Engineering culture reflects delivery", "qualificationsBasic" : "12+ years software engineering, data engineering, DevOps, 7+ years progressive engineering leadership, Managing managers or multi-team organizations, Delivering enterprise-scale platforms and applications, Working in regulated industries, Translate business objectives into technical strategy", "qualificationsPreferred" : "Experience in Managed Services Provider (MSP), Familiarity with ServiceNow development and configuration, Hands-on data platform architecture, Hands-on AI/ML engineering, Hands-on DevOps automation, Experience with AI governance frameworks, Experience with risk management frameworks, Experience with compliance frameworks, Exposure to enterprise data platform design", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Overview We are seeking a highly strategic and execution-focused Sr Director, Data and Application Engineering to lead a broad portfolio of technical teams driving the organization's most critical engineering initiatives. Reporting directly to the Chief Technology Officer (CTO), this leader will oversee four core practice areas — DevOps, Application Development, Data Engineering, and Internal AI Development — and will be responsible for aligning these teams to deliver on the department's strategic goals. As a 1,000-person Managed Services Provider (MSP) serving financial services and healthcare clients, we operate in highly regulated environments that demand secure, compliant, and reliable engineering practices. This leader will ensure all teams operate with the rigor, velocity, and collaboration required to build enterprise-grade platforms and solutions. Reporting Structure Reports to: Chief Technology Officer (CTO) Direct Reports: Engineering leads across DevOps, Application Development, Data Engineering, and AI Development Teams Overseen DevOps Responsible for the infrastructure, CI/CD pipelines, and internal automation capabilities of the organization. This team supports development velocity, reliability, and the continued expansion of automation tooling across internal operations. Application Development Owns the design, development, and ongoing maintenance of internally built applications — most notably the Abacus portal — and supports service delivery initiatives including development and configuration work within ServiceNow. Data Engineering Leads the architecture, construction, and operation of the organization's enterprise data platform, enabling reliable, governed, and scalable data infrastructure across business units. Internal AI Development Drives the development and deployment of AI-powered tools and agents that deliver measurable efficiency gains across the organization. Partners with internal stakeholders to identify, prioritize, and implement AI solutions aligned to business needs. Departmental Goals This role is accountable for organizing and directing all four teams toward the following high-level department objectives: Build and mature the organization's enterprise data platform to support scalable, governed, and insight-ready data infrastructure Assist the service delivery team with the continued development and configuration of ServiceNow to improve ITSM capabilities and operational workflows Expand and integrate the DevOps team's scope to encompass internal automation initiatives, reducing manual effort and improving engineering efficiency across the organization Own the roadmap, development, and ongoing evolution of the internally developed Abacus portal Collaborate with internal stakeholders to identify, prioritize, and deliver AI solutions that drive organizational efficiency and support strategic business outcomes Key Responsibilities Strategic Leadership support career development at all levels Metrics, Reporting & Governance Define and track KPIs across teams (e.g., deployment frequency, platform uptime, data quality, AI adoption, development velocity) Regularly report progress, risks, and outcomes to the CTO and executive leadership Ensure all engineering practices meet governance, compliance, and security standards for regulated environments Qualifications Required 12+ years of experience in software engineering, data engineering, DevOps, or related technical disciplines 7+ years in progressive engineering leadership roles, including managing managers or multi-team organizations Demonstrated experience overseeing multiple, diverse technical teams simultaneously Proven track record of delivering enterprise-scale platforms and applications in production environments Experience working in regulated industries such as financial services, healthcare, or similar Strong ability to translate business objectives into technical strategy and measurable delivery outcomes Excellent executive communication and stakeholder management skills Preferred Experience within a Managed Services Provider (MSP) or services-based technology organization Familiarity with ITSM platforms, particularly ServiceNow development and configuration Hands-on background in one or more of: data platform architecture, AI/ML engineering, or DevOps automation Experience with AI governance, risk management, and compliance frameworks Exposure to enterprise data platform design (e.g., data lakes, lakehouses, data mesh architectures) Key Competencies Strategic vision balanced with pragmatic execution Cross-functional collaboration and executive stakeholder management Organizational design and team development across multiple disciplines Data-driven decision-making and outcomes orientation Clear, compelling communication with both technical and non-technical audiences Ability to lead through ambiguity in a fast-paced, evolving environment Success Metrics (First 12–18 Months) Enterprise data platform foundation is architected, resourced, and delivering initial capabilities ServiceNow development backlog is structured, prioritized, and progressing in partnership with service delivery DevOps automation initiatives are identified, scoped, and delivering measurable efficiency gains Abacus portal roadmap is owned, communicated, and actively progressing At least 2–3 AI solutions are deployed and delivering measurable business value All four engineering teams operate with clear charters, goals, and delivery metrics Engineering culture reflects strong cross-team collaboration and consistent delivery practices Why This Role Matters This role sits at the intersection of platform, product, data, and AI — and is central to the organization's ability to scale, innovate, and operate with excellence. The Senior Director of Engineering will unify four critical engineering functions under a shared vision, accelerating the delivery of the enterprise data platform, modernizing internal tooling, and embedding AI-driven efficiency into the organization's core operations. This is a high-visibility, high-impact leadership role with direct line of sight to the CTO and meaningful influence over the company's long-term technical direction. Benefits of Working for Abacus: Exposure to diverse array of technologies Part of a team of experienced engineers who aim to deliver exceptional service Competitive compensation Performance bonus Robust benefits package: medical, dental, vision, disability, life insurance, 401k, and PTO Opportunities to further technical education through online courses Positive, friendly, supportive work environment", "summaryDescription" : "Sr Director, Data and Application Engineering at ABACUS. Skills: Data Engineering, Application Development, DevOps, AI Development. Lead technical teams. Drive engineering initiatives", "postedDate" : "2026-06-14T19:15:30.605", "createdAt" : "2026-06-14T19:15:30.605", "lastUpdated" : "2026-06-15T21:47:59.306", "ingestTimestamp" : "2026-06-14T19:15:30.605", "mongoId" : "6a2c6a8f74d8ee00a090c9ce", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 245000, "salaryAnnualMax" : 375000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Metrics definition", "KPI tracking", "Risk reporting", "Outcome reporting", "Governance standards", "Compliance standards", "Security standards", "Leadership", "Data Engineering", "Application Development", "DevOps", "AI Development", "Strategic leadership", "Execution focus", "Technical strategy", "Stakeholder management", "Organizational design", "Team development", "Cross-functional collaboration", "Executive communication", "Roadmap planning", "Prioritization", "Regulated environments", "Financial services", "Healthcare", "Managed Services Provider (MSP)", "ITSM platforms", "Data lakes", "Lakehouses", "Data mesh architectures", "ServiceNow" ], "skillCount" : 31, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Director", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2cd70874d8ee00a0a400df", "title" : "AI-Enabled Data Engineer", "company" : "TechTorch", "industry" : "Data", "salary" : { "min" : 115000.0, "max" : 165000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for AI-Enabled Data Engineer in the United States, adjusted for mid-seniority level." }, "location" : "United States", "locations" : [ "United States" ], "timestamp" : "2026-06-16T00:37:23.718", "fingerprint" : "7f7143bd8c116459e8f7cc89021dc5f061aa72daa682ac2f39c89343bf61365e", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/techtorch/878bb1ac-11d2-4d0c-935c-47dc06333917/application", "externalId" : "878bb1ac-11d2-4d0c-935c-47dc06333917", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "remoteFriendly" : true, "rawDescription" : "About TechTorch TechTorch is a high-growth enterprise technology consultancy that partners with the world’s leading private equity-backed businesses. We deliver AI-powered solutions, accelerators, and data-driven transformation initiatives that drive measurable value at speed and scale. Our mission is to redefine enterprise technology consulting for private equity. We combine the agility of a scale-up with the discipline and rigor demanded by the most sophisticated investors and operators. TechTorch was founded by seasoned leaders — including former Bain consultants, CIOs, and tech executives — with deep expertise in technology, transformation, and value creation. We were built to deliver results that matter. About the Practice TechTorch’s Data Practice builds the data infrastructure, platforms, and pipelines that enable organizations to move from raw data to measurable business value. We work across the full data stack — from ingestion and modeling to AI-ready data products — and we move fast by letting AI do the heavy lifting wherever it can. This role sits at the intersection of deep data engineering craft and modern AI capability. Data engineering is your foundation. AI is your force multiplier. What You’ll Do Data Engineering & Platform - Design, build, and maintain scalable data pipelines and ETL/ELT workflows across cloud and on-prem environments. - Work with Snowflake, Databricks, and Delta Lake as primary data platforms — handling ingestion, transformation, storage optimization, and access patterns. - Model data with dbt: write modular SQL transformations, manage dependencies, enforce data contracts, and maintain documentation. - Build and maintain semantic layers that serve consistent, governed metrics to downstream consumers. - Design data warehouse schemas and data lake structures that balance performance, cost, and queryability. - Implement data quality frameworks — testing, validation, alerting, and lineage — as first-class citizens in every pipeline. Orchestration & Operations - Orchestrate workflows across Airflow, Dagster/Prefect, Azure Data Factory, and Databricks Workflows — choosing the right tool for each job. - Apply DataOps practices: CI/CD for data pipelines, environment promotion, infrastructure as code, and observability. - Own the reliability of data products end-to-end — monitoring, alerting, incident response, and root cause analysis. - Work across AWS and Azure cloud services (S3, Glue, ADLS, ADF, Synapse, Redshift) to design cost-effective, scalable architectures. AI-Enabled Data Engineering - Build data pipelines that feed AI systems — including RAG ingestion workflows, vector store loading, document chunking, and embedding pipelines. - Use LLMs as active components in ETL logic: classification, entity extraction, enrichment, and data quality remediation in-flight. - Expose data infrastructure as consumable tools for AI agents via MCP or similar agent-integration patterns. - Use AI-paired programming (Claude Code or equivalent) as a daily productivity layer — not just autocomplete, but genuine workflow acceleration. - Stay current on how AI tooling changes the data engineering workflow and bring those patterns back to the team. What You Bring Core Data Engineering: ETL/ELT Design · Data Modeling · Data Quality & Testing · Data Lineage · Batch & Incremental Loads Data Platforms: Snowflake · Databricks · Apache Spark / PySpark · Delta Lake · Data Warehouses · Data Lakes Transformation & Modeling: dbt Core / dbt Cloud · SQL (advanced) · Semantic Layer · Dimensional Modeling Orchestration: Apache Airflow · Dagster / Prefect · Azure Data Factory · Databricks Workflows AI-Enabled Engineering: RAG & Vector Store Pipelines · AI-Augmented ETL · MCP / Agent Data Tools · AI-Paired Programming · LLM Integration in Pipelines Cloud & DevOps: AWS (S3, Glue, Redshift) · Azure (ADLS, ADF, Synapse) · CI/CD for Data · Infrastructure as Code · Python Nice to Have - Experience with streaming architectures: Kafka, Spark Streaming, or Flink. - Exposure to feature stores (Feast, Tecton) or ML platform data pipelines. - Hands-on with vector databases: Pinecone, Weaviate, Qdrant, or pgvector. - Familiarity with data mesh or data product ownership models. - Experience with Snowpark or Databricks AI/BI tooling. - Building or contributing to internal data tooling, frameworks, or accelerators. What We Offer - Work on real, complex data problems across multiple client environments — not toy datasets. - A team that takes AI tooling seriously and expects you to use it, not just know it. - Access to the full modern data stack — no one-tool shops. - Room to grow into data architecture, platform leadership, or AI engineering depending on where you want to take it. - Collaborative culture that values opinions, craft, and intellectual curiosity.", "summaryDescription" : "AI-Enabled Data Engineer at TechTorch", "createdAt" : "2026-06-14T20:14:21.346", "lastUpdated" : "2026-06-16T00:37:23.718", "ingestTimestamp" : "2026-06-14T20:14:21.346", "mongoId" : "6a2cd70874d8ee00a0a400df", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 115000, "salaryAnnualMax" : 165000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "hasLocation" : true, "hasGeo" : false, "llmIndustryConfidence" : 0.98 }, { "id" : "6a30511af292fd229cefa697", "title" : "Sr Director Analyst - AI and Software Engineering", "industry" : "Analyst", "salary" : { "min" : 240000.0, "max" : 360000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Director-level AI and Software Engineering role in the US technology industry, adjusted for seniority and remote work." }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T12:05:32.334", "fingerprint" : "17bfe148d7427676d479bc47b35363f4c7b8ce12ad72aa97f7423a11d8d576ab", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/e23cc334-09a9-4253-8570-0ab055a44716/apply", "externalId" : "e23cc334-09a9-4253-8570-0ab055a44716", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 12, "experienceLevel" : "Director", "technicalSkills" : "AI, LLMs, OpenAI GPT, Anthropic Claude, Coding agents, Copilots", "professionalSkills" : [ "SDLC transformation", "AI-enabled application design", "Strategic guidance", "Software architecture", "Development practices" ], "hardSkillsList" : [ "Market trend analysis", "Data synthesis", "Strategic decision-making" ], "hardSkills" : [ { "name" : "Market trend analysis", "level" : "intermediate" }, { "name" : "Data synthesis", "level" : "intermediate" }, { "name" : "Strategic decision-making", "level" : "intermediate" } ], "majorSkills" : "AI, Software Engineering, LLMs", "majorSkillsList" : [ "AI", "Software Engineering", "LLMs" ], "coreResponsibilities" : "Develop and publish research, Analyze emerging technology and market trends, Advise clients directly, Reframe complex client challenges, Recommend future-ready approaches, Create and deliver presentations, Act as a market voice, Shape thought leadership, Shape client engagement strategies, Represent research insights externally, Contribute to peer review, Contribute to research innovation, Contribute to cross-team collaboration, Mentor junior analysts, Contribute to team development", "teamCollaboration" : "Global, multicultural teams; Sales and internal research teams", "domainKnowledge" : "AI-native development; Enterprise software development; AI agents; LLMs; Coding copilots; AI architectures; Custom-built enterprise software", "domainList" : [ "ai-native-development", "enterprise-software-development", "ai-agents", "llms", "coding-copilots", "ai-architectures", "custom-built-enterprise-software" ], "domainSpecificKnowledge" : [ "AI-native development", "Enterprise software development", "AI agents", "LLMs", "Coding copilots", "AI architectures", "Custom-built enterprise software" ], "communicationSkills" : "Executive briefings; Keynote content; Storytelling skills", "documentationSkills" : "Research outputs", "continuousLearning" : "Professional development opportunities", "innovationCreativity" : "Research innovation", "problemSolvingSkills" : "Root cause analysis", "specialRequirements" : "Travel up to 25%", "qualificationsBasic" : "Bachelor's degree, 12+ years of relevant experience, Deep expertise in AI-driven software development, Knowledge of leading LLM ecosystems, Hands-on understanding of AI architectures, Proven ability to analyze market trends, Exceptional executive presence, Research, writing, and storytelling skills, Advanced presentation skills, Analytical ability to synthesize data, Excellent business and financial acumen, Ability to work independently, Organizational skills", "qualificationsPreferred" : "Media experience, External visibility", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "## Accountabilities Develop and publish high-impact, “must-have” research focused on AI, software engineering, and AI-native development practices for global technology leaders. Analyze emerging technology and market trends, including AI agents, LLMs, and coding copilots, to identify strategic implications for enterprise software development. Advise clients directly through executive briefings, on-site engagements, and global conferences, helping them translate insights into actionable strategies. Reframe complex client challenges by identifying root causes and recommending future-ready approaches to software architecture and development. Create and deliver high-quality presentations, keynote content, and research outputs for senior technology and business audiences. Act as a market voice in collaboration with sales and internal research teams to shape thought leadership and client engagement strategies. Represent research insights externally through media, industry events, and professional networks, strengthening credibility and influence. Contribute to peer review, research innovation, and cross-team collaboration while mentoring junior analysts and contributing to team development. Requirements: Bachelor’s degree required; 12+ years of relevant experience in software engineering, AI, or related technical leadership roles (or equivalent experience). Deep expertise in AI-driven software development, including SDLC transformation and AI-enabled application design. Strong knowledge of leading LLM ecosystems (e.g., OpenAI GPT, Anthropic Claude) and developer tools such as coding agents and copilots. Hands-on understanding of AI architectures, including agents and systems used in custom-built enterprise software. Proven ability to analyze market trends and translate them into strategic guidance for enterprise technology leaders. Exceptional executive presence with the ability to engage and influence C-level stakeholders. Strong research, writing, and storytelling skills, including the ability to create compelling visual and analytical content. Advanced presentation skills with experience delivering keynote-level content to large or executive audiences. Strong analytical ability to synthesize data from interviews, surveys, and market research into structured insights. Excellent business and financial acumen to support strategic decision-making in complex environments. Ability to work independently while collaborating effectively across global, multicultural teams. Strong organizational skills with the ability to manage high-profile deliverables under tight deadlines. Willingness to travel up to 25% as needed. Media experience and external visibility are highly desirable. Benefits: Competitive base salary ranging from $172,000 to $202,500 USD, depending on experience and qualifications. Annual performance-based bonus or uncapped incentive compensation (role dependent). Comprehensive healthcare coverage including medical, dental, vision, life, and disability insurance. Generous paid time off and hybrid working flexibility with remote-first options when appropriate. 401(k) retirement plan with employer match (up to $7,200 annually). Employee stock purchase program with discounted company stock options. Access to world-class research resources, tools, and global thought leadership platforms. Strong professional development opportunities in a highly visible, global AI leadership environment. Inclusive, collaborative workplace culture with global exposure and cross-industry engagement. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Sr Director Analyst - AI and Software Engineering. Skills: AI, Software Engineering, LLMs. Develop and publish research. Analyze emerging technology and market trends", "postedDate" : "2026-06-15T10:33:04.630", "createdAt" : "2026-06-15T10:33:04.630", "lastUpdated" : "2026-06-16T12:05:32.334", "ingestTimestamp" : "2026-06-16T03:21:43.030", "mongoId" : "6a30511af292fd229cefa697", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 240000, "salaryAnnualMax" : 360000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Market trend analysis", "Data synthesis", "Strategic decision-making", "AI", "Software Engineering", "LLMs", "SDLC transformation", "AI-enabled application design", "Strategic guidance", "Software architecture", "Development practices", "AI-native development", "Enterprise software development", "AI agents", "Coding copilots", "AI architectures", "Custom-built enterprise software" ], "skillCount" : 17, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6960822f0937eae70e9c7ff0", "title" : "Quality and Insights Manager", "company" : "Home Group", "salary" : { "min" : 40000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : false }, "location" : "Tyne and Wear-Newcastle upon Tyne-Newcastle upon Tyne (Strawberry Lane)", "locations" : [ "Tyne and Wear-Newcastle upon Tyne-Newcastle upon Tyne (Strawberry Lane)", "18.Jan.26, 11:59:00 PM", "242570, 242570, true" ], "timestamp" : "2026-06-15T11:57:45.075", "fingerprint" : "4b9f2cf4840138e705560c1bd8e964c5a6230bfec82b31df2e3b0287238c5c7d", "source" : "taleo", "language" : "en", "applyUrl" : "https://homegroup.taleo.net/careersection/ex/jobdetail.ftl?job=242570", "externalId" : "242570", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Newcastle upon Tyne", "state" : "Tyne and Wear", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "54.9738474,-1.6131572" } ], "locationText" : "Newcastle upon Tyne, Tyne and Wear, United Kingdom", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "professionalSkills" : [ "Process management", "Cross-functional coordination", "Vendor management", "Stakeholder management", "Operational metrics", "Resource planning", "Continuous improvement" ], "hardSkillsList" : [ "Audit analysis", "Feedback analysis", "Action planning", "Team management", "Coaching support", "Training program management", "Performance improvement", "Process management", "Standards management", "Needs spotting", "Customer voice integration" ], "hardSkills" : [ { "name" : "Audit analysis", "level" : "intermediate" }, { "name" : "Feedback analysis", "level" : "intermediate" }, { "name" : "Action planning", "level" : "intermediate" }, { "name" : "Team management", "level" : "intermediate" }, { "name" : "Coaching support", "level" : "intermediate" }, { "name" : "Training program management", "level" : "intermediate" }, { "name" : "Performance improvement", "level" : "intermediate" }, { "name" : "Process management", "level" : "intermediate" }, { "name" : "Standards management", "level" : "intermediate" }, { "name" : "Needs spotting", "level" : "intermediate" }, { "name" : "Customer voice integration", "level" : "intermediate" } ], "majorSkills" : "Quality assurance, Customer insights, Team leadership, Continuous improvement", "majorSkillsList" : [ "Quality assurance", "Customer insights", "Team leadership", "Continuous improvement" ], "coreResponsibilities" : "Build quality assurance framework, Manage quality assurance framework, Drive excellent customer outcomes, Drive brilliant colleague experience, Turn checks into insights, Turn audits into insights, Turn feedback into insights, Suggest actions from insights, Manage coaches, Support coaches, Manage trainer, Support trainer, Ensure training programme is insight-driven, Ensure coaching support is insight-driven, Improve performance, Help leaders understand performance, Help teams understand performance, Drive continuous improvement culture, Keep processes fresh, Keep standards fresh, Spot training needs, Put support in place, Make customer voice central", "teamCollaboration" : "Work with leaders; Work with team; Work with L&D", "domainKnowledge" : "Customer service; Regulated setting", "domainList" : [ "customer-service", "regulated-setting" ], "domainSpecificKnowledge" : [ "Customer service", "Regulated setting" ], "communicationSkills" : "Share feedback", "continuousLearning" : "Grow career support; Learning support", "innovationCreativity" : "Shape something new", "problemSolvingSkills" : "Analytical skills; Problem-solving skills", "outcomesObjectives" : "Drive changes that matter; Improve customer experiences; Ensure right service first time", "qualificationsBasic" : "Line management experience, Contact centre experience, Customer service environment experience, Quality management qualification, Auditing qualification, Equivalent experience in setting up quality assurance, Equivalent experience in managing quality assurance, Analytical skills, Problem-solving skills, Clear timely feedback skills, Communication skills, Influencing skills, Collaborative approach, Passion for coaching, Helping others grow, Build something new, Take people on journey", "qualificationsPreferred" : "Coaching and training a new team experience", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Quality & Insights Manager Newcastle upon Tyne, hybrid working minimum 2 days office based per week Permanent, full time (37.5 hpw) Earn £40,000 pa, with bril liant benefits! ‘Previous applicants need not apply’ Home, a place where you belong You know that great service doesn’t happen by accident. It’s built on care, consistency and a clear picture of how we’re doing. If you’ve ever thought “there’s a better way to do this” and wanted the space to make it happen, this could be your moment. We’re looking for someone who can bring quality assurance to life, not just in processes, but in how our colleagues work together, learn and grow. With experience of coaching and training a new team. You’ll be the person who spots what’s going well, sees where we can improve, and turns that into insight that will drive changes that really matter for our customers. You’ll join our friendly Customer Service Quality and Improvement team, where we work hard to make sure every customer gets the right service, first time. You’ll have the freedom to dig deep into the details to share insights and manage the actions that drive better customer experiences. What you’ll do Build and manage a simple, consistent quality assurance framework that works for everyone and drives excellent customer outcomes and brilliant colleague experience. Turn checks, audits and feedback into clear insights and suggested actions Manage and support a team of coaches and a trainer, ensuring the training programme and coaching support are insight-driven and focused on improving performance Work with leaders and team to help them understand how we are performing and drive a continuous improvement culture within the team Keep our processes and standards fresh, relevant and fit for the future Spot training needs quickly and working with our trainer along with L&D to put the right support in place Make sure the customer’s voice is at the heart of every change we make Why choose us Imagine finishing each day knowing you’ve made a real difference in our customers’ lives. That’s exactly what you’ll do here, working for a top 10 Great Place to Work in the UK! You’ll have space to grow, support to learn, and the chance to shape something brand new. What you bring Strong line management experience. Experience of working in a contact centre or customer service environment. A qualification in quality management, auditing, or equivalent experience in setting up or managing quality assurance in a regulated setting A curious mind with great analytical and problem-solving skills The confidence to share clear timely feedback that drives action Strong communication and influencing skills with a collaborative approach Passion for coaching and helping others grow Enthusiasm to build something new and take people on the journey with you Job details You’ll work Monday to Friday This is a hybrid role, and you’ll spend a minimum of 2 days in our One Strawberry Lane office, and the rest working from home A place where you belong We do our best work when we can be ourselves. That’s why inclusion and wellbeing shape our policies and daily practice. Our diversity networks, Multicultural, LGBTQIA+, Women, and Disability, along with peers and allies, help us thrive. Together we make Home Group a great place to work ! What’s in it for you? Enjoy 34 days leave (this includes bank holidays and a \"me day\"!), and the option to buy five days more (subject to criteria). 2 days paid volunteering Generous pension and 3x salary life insurance. Check more benefits online! Save up to £1140 yearly with our health cash plan, covering dental, optical, and therapies. 800+ discounts or cashback on shopping, holidays, and more. We’re a top 10 UK Wellbeing employer; our tools and support are here when you need them! Grow your career with us, we’ll help you take the next step. Ready to join us? Click APPLY NOW to see the Quality & Insights Manager job description , learn about us , and for help to apply . Don’t wait, roles can close early, so apply and take the first step towards making a difference. To let us know how we can help you shine in our process, email recruitment@homegroup.org.uk to discuss your reasonable adjustments. Newcastle upon Tyne (Strawberry Lane)", "summaryDescription" : "Quality and Insights Manager at Home Group. Skills: Quality assurance, Customer insights, Team leadership, Continuous improvement. Build quality assurance framework. Manage quality assurance framework", "createdAt" : "2026-06-14T01:52:38.205", "lastUpdated" : "2026-06-15T11:57:45.075", "ingestTimestamp" : "2026-06-14T01:52:38.205", "mongoId" : "6960822f0937eae70e9c7ff0", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Audit analysis", "Feedback analysis", "Action planning", "Team management", "Coaching support", "Training program management", "Performance improvement", "Process management", "Standards management", "Needs spotting", "Customer voice integration", "Quality assurance", "Customer insights", "Team leadership", "Continuous improvement", "Cross-functional coordination", "Vendor management", "Stakeholder management", "Operational metrics", "Resource planning", "Customer service", "Regulated setting" ], "skillCount" : 22, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Manager", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Real Estate", "llmIndustryConfidence" : 0.92 }, { "id" : "6a3058bdf292fd229cf43fac", "title" : "Customer Service and Sales Representative - Seasonal", "company" : "Sourcefit", "salary" : { "min" : 315000.0, "max" : 420000.0, "currency" : "PHP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level Customer Service and Sales Representative in Quezon City, Philippines, adjusted for the Outsource industry and contract employment type." }, "location" : "Bridgetowne Quezon City, PH", "locations" : [ "Bridgetowne Quezon City", "PH" ], "timestamp" : "2026-06-16T08:09:38.877", "fingerprint" : "63ce3206f04ba697035ba2fdcc8e0d767f715cfef9fdb34af6e47343613b1625", "source" : "breezyhr", "language" : "en", "applyUrl" : "https://sourcefit.breezy.hr/p/01cfd0244d48-customer-service-and-sales-representative-seasonal", "externalId" : "01cfd0244d48", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Quezon City", "state" : "Metro Manila", "country" : "Philippines", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "14.6510546,121.0486254" } ], "locationText" : "Quezon City, Metro Manila, Philippines", "employmentType" : "CONTRACT", "coreResponsibilities" : "Provide customer service, Process sales orders, Handle customer inquiries, Upsell products and services, Meet sales targets", "communicationSkills" : "Customer service; Sales", "outcomesObjectives" : "Meet sales targets", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "summaryDescription" : "Customer Service and Sales Representative - Seasonal at Sourcefit. Provide customer service. Process sales orders", "createdAt" : "2026-06-15T22:12:12.310", "lastUpdated" : "2026-06-16T08:09:38.877", "ingestTimestamp" : "2026-06-15T22:12:12.310", "mongoId" : "6a3058bdf292fd229cf43fac", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "sales", "jobSubcategory" : "revenue", "seniorityLevel" : "Entry", "dataQualityScore" : 0.5555556, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Outsource", "llmIndustryConfidence" : 0.85 }, { "id" : "6a191e7758b93c861e39f74d", "title" : "Senior Data & AI Engineer", "salary" : { "min" : 2500000.0, "max" : 4500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Data & AI Engineer in Bangalore, India, adjusted for seniority and the technology industry." }, "location" : "India-Karnataka-Bangalore", "locations" : [ "India-Karnataka-Bangalore", "Brigade Tech Gardens, Katha No. 119, Kundalahalli Village, K.R. Puram Hobli, Ward No. 85, Bangalore" ], "timestamp" : "2026-06-15T22:31:31.403", "fingerprint" : "56de1627424f531e877b8224fa52803dac62de6f68a879bc426c31eb78c2761d", "source" : "taleo", "language" : "en", "applyUrl" : "https://tas-daimler.taleo.net/careersection/ex/jobdetail.ftl?job=896114", "externalId" : "896114", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bangalore", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bangalore, Karnataka, India", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "remoteFriendly" : false, "rawDescription" : "Senior Data & AI Engineer – Data & AI Platform We are looking for a Senior Data & AI Engineer to design, build, and operationalize scalable AI/ML solutions within our Data and AI Platform. This role focuses on enabling enterprise-wide AI adoption by developing robust data pipelines, deploying ML models, and building reusable AI services aligned with platform standards. You will work at the intersection of Data Engineering, Machine Learning, and Platform Architecture , ensuring AI solutions are production-ready, governed, observable, secure, and cost-efficient. Key Responsibilities 1. AI/ML Solution Development Design and implement scalable Machine Learning and Generative AI solutions on Databricks and Azure/AWS Build and optimize feature engineering pipelines and training workflows Develop reusable AI components, APIs, and enterprise AI services 2. Platform & MLOps Enablement Build and maintain end-to-end ML pipelines including training, validation, deployment, and monitoring Implement CI/CD pipelines for ML models and AI applications Integrate AI workloads with tools such as: Databricks MLflow Unity Catalog 3. Data Engineering & Integration Collaborate with Data Engineers to ensure high-quality and governed datasets Work with both structured and unstructured data across batch and streaming pipelines Optimize data pipelines for performance, scalability, and cost efficiency 4. AI Governance & Observability Implement model monitoring, drift detection, and performance tracking Ensure compliance with AI governance, security, and regulatory standards Enable auditability, lineage tracking, and observability for AI models Required Skills & Qualifications Advanced Data Engineering – Databricks Ecosystem Databricks Platform Expertise Strong hands-on experience with the Databricks ecosystem, including: Delta Lake Delta Live Tables Unity Catalog Databricks Workflows Serverless Compute Mosaic AI Model Serving Endpoints Data Pipeline Engineering Build scalable batch and streaming pipelines using: Apache Spark Structured Streaming Apache Kafka Additional expertise required in: Medallion Architecture (Bronze / Silver / Gold) CDC implementation and incremental processing strategies Schema evolution and data contract enforcement Performance Optimization Query tuning and execution plan optimization Partitioning, clustering, and Z-ordering Cost optimization for Databricks workloads Autoscaling and workload sizing strategies Foundation Models & Generative AI Engineering Foundation Model Experience Hands-on experience with enterprise usage of: OpenAI models Anthropic models Meta Llama family Google Gemini Mistral AI models Open-source deployment patterns Model Engineering Fine-tuning and instruction tuning LoRA / QLoRA optimization Quantization strategies Model serving and inference optimization LLMOps Prompt lifecycle management Evaluation pipelines for LLM outputs Hallucination mitigation Guardrails and output validation Retrieval-Augmented Generation (RAG) & Knowledge Systems RAG Architecture Design and implementation of production-grade RAG systems Hybrid retrieval strategies Context window optimization Chunking and embedding strategies Vector Databases Hands-on experience with: FAISS Pinecone Milvus Databricks Vector Search Embedding Systems Embedding model selection and benchmarking Semantic search optimization Knowledge indexing pipelines AI Agent & Multi-Agent Systems Agentic AI Development Design of autonomous and semi-autonomous AI agents Tool-calling orchestration Workflow-based reasoning systems Memory management strategies Multi-Agent Systems (MAS) Agent coordination patterns Task decomposition frameworks Agent collaboration protocols Conflict resolution strategies Experience with: LangChain LangGraph AutoGen AI Communication Protocols & Integration Standards Model Context Protocol (MCP) Building and deploying MCP-compliant servers Tool exposure and orchestration Secure model-tool interaction design Agent-to-Agent (A2A) Protocols Understanding inter-agent communication patterns Event-driven agent coordination Distributed AI workflow orchestration API & Service Mesh Integration REST / gRPC service integration Event-driven AI services Enterprise service bus integration Modern AI Platform Engineering Serving Infrastructure Real-time inference serving Batch inference pipelines Autoscaling inference endpoints Containerization & Orchestration Docker Kubernetes Helm deployment patterns Emerging AI Platform Standards Experience with MCP server development Exposure to A2A communication protocols AI agent orchestration platforms Enterprise-grade tool-use governance Databricks AI Platform Experience with: Mosaic AI Agent Framework Databricks Vector Search AI Gateway Lakehouse Monitoring Nice-to-Have Use Case Exposure AI copilots for data engineering workflows Autonomous data quality remediation Metadata-aware AI systems Semantic data discovery Agentic ETL orchestration Natural language-to-SQL systems Enterprise knowledge assistants LLM-powered observability platforms Mercedes-Benz Research and Development India Private Limited", "summaryDescription" : "Senior Data & AI Engineer", "createdAt" : "2026-06-14T21:53:18.038", "lastUpdated" : "2026-06-15T22:31:31.403", "ingestTimestamp" : "2026-06-14T21:53:18.038", "mongoId" : "6a191e7758b93c861e39f74d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.5555556, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a0f529b58b93c861e052fca", "title" : "Sr. Manager, Customer Performance & Insights", "company" : "Hyundai Capital America", "location" : "United States-California-Irvine", "locations" : [ "United States-California-Irvine", "
Headquarters 1 (HCA_HQ1)
3161 Michelson Dr. Ste 1900
Irvine, 92612

" ], "timestamp" : "2026-06-15T13:57:07.233", "fingerprint" : "71c876584c8bc802443fa6a9717e593495b85bf227c1884721d5d702f910419a", "source" : "taleo", "applyUrl" : "https://hyundaicapital.taleo.net/careersection/ex/jobdetail.ftl?job=116564", "externalId" : "116564", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Irvine", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid" } ], "locationText" : "Irvine, California, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor", "experienceMinYears" : 8, "experienceLevel" : "Manager", "technicalSkills" : "SQL, Python", "professionalSkills" : [ "Customer experience, financing, leasing, insurance solutions." ], "hardSkillsList" : [ "SQL", "Python" ], "softSkillsList" : [ "leadership" ], "hardSkills" : [ { "name" : "SQL", "level" : "intermediate" }, { "name" : "Python", "level" : "intermediate" } ], "softSkills" : [ { "name" : "leadership" } ], "majorSkills" : "customer insights, CX analytics, predictive analytics, stakeholder management, leadership", "majorSkillsList" : [ "customer insights, CX analytics, predictive analytics, stakeholder management, leadership" ], "coreResponsibilities" : "Responsible for delivering a comprehensive, real-time view of customer experience performance across the enterprise. Builds and oversees the full ecosystem of customer feedback to uncover actionable insights, identify experience gaps, and guide business stakeholders toward data-driven, customer-focused improvements.", "teamCollaboration" : "Facilitate cross-functional alignment and embed customer-driven decision-making.", "toolProficiency" : [ "Glassbox, Microsoft Office" ], "communicationSkills" : "executive-level communication; storytelling; executive presentation", "problemSolvingSkills" : "analytical; problem-solving", "specialRequirements" : "Work model is onsite 4 days a week. Compliance with all applicable federal, state, and local equal employment opportunity laws. California Privacy Notice provided.", "outcomesObjectives" : "Identify customer pain points and journey friction by connecting insights across touchpoints, behavioral data, and feedback signals. Develop dashboards, scorecards, and executive reporting that shift from reactive reporting to proactive, predictive CX management. Establish proactive monitoring and predictive analytics to detect emerging CX risks. Design and manage closed-loop feedback systems to ensure resolution and measurable improvements.", "qualificationsBasic" : "8+ years in customer insights, CX analytics, research, VoC, or CX strategy. 3+ years of leadership experience. Predictive analytics experience related to customer behavior or journey risk. Experience managing qualitative, quantitative, and behavioral research programs. Proven ability to influence senior stakeholders and lead cross-functional initiatives. Executive-level communication experience. Bachelor’s degree in relevant field required.", "qualificationsPreferred" : "Advanced degree preferred. Familiarity with CX tools (e.g., Glassbox).", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Job Title: Sr. Manager, Customer Performance & Insights Hyundai Capital America (HCA) helps people move forward. Through Hyundai Motor Finance, Genesis Finance, and Kia Finance, we deliver innovative financing, leasing, and insurance solutions to more than 3 million customers and businesses nationwide. We’re a company driven by growth, innovation, and people. At HCA, you’ll find opportunities to build new skills, expand your career, and make a real impact—while working in a diverse, inclusive, and values driven environment. We’re proud to support our communities through volunteerism, philanthropy, and engaged Employee Resource Groups. If you’re looking for a fast paced, collaborative workplace where your ideas matter, join us as we lead the future of financing freedom of movement. Apply today. WORK MODEL #LI-OnSite (4 days a week) WHAT YOU WILL DO The Sr. Manager, Customer Performance & Insights is a strategic analytics leader responsible for delivering a comprehensive, real-time view of customer experience performance across the enterprise. This role builds and oversees the full ecosystem of customer feedback—both stated and unstated—to uncover actionable insights, identify experience gaps, and guide business stakeholders toward data-driven, customer-focused improvements. HOW YOU WILL MAKE AN IMPACT Own and evolve the enterprise CX Health measurement framework, integrating feedback across channels to deliver a holistic view of customer experience Identify customer pain points and journey friction by connecting insights across touchpoints, behavioral data, and feedback signals Develop dashboards, scorecards, and executive reporting that shift from reactive reporting to proactive, predictive CX management Lead customer research and analytics programs, translating findings into actionable, prioritized recommendations Integrate insights from social media, call centers, complaints, operational data, and tools like Glassbox Establish proactive monitoring and predictive analytics to detect emerging CX risks Facilitate cross-functional alignment and embed customer-driven decision-making Design and manage closed-loop feedback systems to ensure resolution and measurable improvements Influence senior stakeholders through storytelling and data-backed recommendations Lead, mentor, and develop a high-performing team WHAT YOU WILL BRING TO THE ROLE Experience: 8+ years in customer insights, CX analytics, research, VoC, or CX strategy 3+ years of leadership experience Predictive analytics experience related to customer behavior or journey risk Experience managing qualitative, quantitative, and behavioral research programs Proven ability to influence senior stakeholders and lead cross-functional initiatives Executive-level communication experience Education: Bachelor’s degree in relevant field required Advanced degree preferred Skills & Knowledge: Expertise in customer insights, VoC, and CX measurement Strong analytical and problem-solving skills Experience with SQL, Python, or predictive modeling tools Ability to translate data into actionable strategies Familiarity with CX tools (e.g., Glassbox) Strong storytelling and executive presentation skills Stakeholder management in matrixed environments Advanced Excel and Microsoft Office skills Strong communication and leadership abilities WE TAKE CARE OF OUR PEOPLE Along with competitive pay, as an employee of HCA, you are eligible for: · Medical, dental, and vision plans with no-cost and low-cost options · Annual employer HSA contribution · 401(k) matching and immediate vesting · Vehicle purchase and lease discounts, plus monthly vehicle allowances by job level: o Associate / Sr. Associate: $350 o Manager / Sr. Manager: $600 o Director: $800 o Executive Director: $900 o VP or Above: $1,000 · 100% employer-paid life and disability insurance · No-cost health and wellbeing programs, including a gym benefit · Six weeks of paid parental leave · Paid Volunteer Time Off, plus a company donation to a charity of your choice WHAT HAPPENS NEXT Express your interest by submitting an application. Our recruiting team will review your application to assess alignment with the role. Visit our careers page to learn more about our culture. OTHER DETAILS Work Environment & Physical Requirements: Extended sitting, standing, and screen time in a hybrid work environment (office and remote). Our Company is an equal opportunity employer committed to fostering a diverse, inclusive, and respectful workplace—because we believe diversity builds stronger teams. We comply with all applicable federal, state, and local equal employment opportunity laws and do not discriminate on the basis of race, religion or creed, color, national origin, ancestry, caste, citizenship, sex or gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, medical condition, genetic information, marital status, family care or medical leave status, military or veteran status, political affiliation, or any other characteristic protected by law. Information provided during the application process is requested in good faith and will be used solely in accordance with applicable employment laws. California Privacy Notice This notice only applies to our applicants who reside in the State of California. The latest version of our Privacy Policy can be found here . This Privacy Policy provides you with notice, at or before the point of collection, about the categories of personal information to be collected from you, the purposes for which your personal information is collected or used, and whether that information is sold or shared, so that you can exercise meaningful control over our use of your personal information. We are providing this notice to comply with the California Consumer Privacy Act of 2018, as amended as amended by the California Privacy Rights Act of 2020 (“CCPA”). If you have any questions about CCPA regarding California residents or HCA team members, please contact the Privacy Team at Privacy2@hcs.com . United States-California-Irvine", "summaryDescription" : "Sr. Manager, Customer Performance & Insights at Hyundai Capital America. Skills: customer insights, CX analytics, predictive analytics, stakeholder management, leadership. Responsible for delivering a comprehensive, real-time view of customer experience performance across the enterprise. Builds and oversees the full ecosystem of customer feedback to uncover actionable insights, identify experience gaps, and guide business stakeholders toward data-driven, customer-focused improvements.", "createdAt" : "2026-06-14T20:47:45.690", "lastUpdated" : "2026-06-15T13:57:07.233", "ingestTimestamp" : "2026-06-14T20:47:45.690", "mongoId" : "6a0f529b58b93c861e052fca", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "hasSalary" : false, "allSkills" : [ "SQL", "Python", "leadership", "customer insights, CX analytics, predictive analytics, stakeholder management, leadership", "Customer experience, financing, leasing, insurance solutions.", "Glassbox, Microsoft Office" ], "skillCount" : 6, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Manager", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c692274d8ee00a09062a3", "title" : "Engineering — Full Stack AI Engineer", "company" : "Sarvam", "industry" : "Engineering", "salary" : { "min" : 2200000.0, "max" : 3500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Full Stack AI Engineer in Bengaluru, India, adjusted for the technology industry and company size." }, "location" : "Bengaluru", "locations" : [ "Bengaluru" ], "timestamp" : "2026-06-15T21:21:41.453", "fingerprint" : "7349e6ae284d19d2e571f955faff09d31f265f4509b1ba3f35d00a7a21b3d95e", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/sarvam/325c7d1b-963d-42a8-b2b8-a4c5c6705c54/application", "externalId" : "325c7d1b-963d-42a8-b2b8-a4c5c6705c54", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Python, Node.js, React, Next.js, AWS, GCP, Azure, AI/ML models", "professionalSkills" : [ "System design", "Product sense" ], "hardSkillsList" : [ "Full stack engineering", "Backend development", "Frontend development", "API integration", "Data pipelines" ], "hardSkills" : [ { "name" : "Full stack engineering", "level" : "intermediate" }, { "name" : "Backend development", "level" : "intermediate" }, { "name" : "Frontend development", "level" : "intermediate" }, { "name" : "API integration", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" } ], "majorSkills" : "Full Stack AI, Backend services, Frontend interfaces, AI model integration", "majorSkillsList" : [ "Full Stack AI", "Backend services", "Frontend interfaces", "AI model integration" ], "coreResponsibilities" : "Build and ship full stack features, Integrate AI models, Design scalable backend services, Maintain scalable backend services, Design data pipelines, Maintain data pipelines, Develop frontend interfaces, Manage product portfolio lifecycle, Collaborate with product teams, Collaborate with design teams, Collaborate with GTM teams, Monitor production systems, Debug issues, Improve reliability, Improve performance, Improve user experience, Contribute to technical architecture, Define engineering standards", "teamCollaboration" : "Product teams; Design teams; GTM teams; Business teams", "projectManagementSkills" : [ "Scoping", "Prioritisation", "Deployment", "Iteration" ], "domainKnowledge" : "Sovereign AI; Indian AI platform; Speech capabilities; Language capabilities; Multimodal capabilities; Education sector; EdTech platforms; Indian language contexts; Tier 2/3 markets", "domainList" : [ "sovereign-ai", "indian-ai-platform", "speech-capabilities", "language-capabilities", "multimodal-capabilities", "education-sector", "edtech-platforms", "indian-language-contexts", "tier-2-3-markets" ], "domainSpecificKnowledge" : [ "Sovereign AI", "Indian AI platform", "Speech capabilities", "Language capabilities", "Multimodal capabilities", "Education sector", "EdTech platforms", "Indian language contexts", "Tier 2/3 markets" ], "problemSolvingSkills" : "Debugging", "qualificationsBasic" : "3–5 years full stack engineering experience, Backend development (Python, Node. js, or equivalent), Frontend frameworks (React, Next. js, or equivalent), Integrating AI/ML models or APIs, System design, RESTful APIs, Cloud infrastructure (AWS, GCP, or Azure), Manage multiple workstreams, Product sense", "qualificationsPreferred" : "Building products for education sector, Speech or NLP technologies, Indian language contexts, Low-bandwidth or mobile-first product design", "workSiteFlexibility" : "Flexible", "rawDescription" : "ABOUT SARVAM Sarvam is building the bedrock of Sovereign AI for India. The company is developing India's full-stack sovereign AI platform, building across research, models, infrastructure and applications with a singular focus on making AI genuinely work for India. Sarvam works with leading enterprises and public institutions and is backed by Lightspeed, Peak XV, and Khosla Ventures. Sarvam partners with India's leading brands, including Tata Capital, SBI Life, CRED, IDFC, and LIC. ABOUT THE ROLE We are looking for a Full Stack AI Engineer with 3–5 years of experience to build and manage Sarvam's education product portfolio. You will work across the full stack — from AI model integration and backend services to frontend experiences — shipping products that reach learners, educators, and institutions at scale. This is a high-ownership engineering role where you will shape both the technical architecture and the product direction of Sarvam's education vertical. WHAT YOU'LL DO • Build and ship full stack features across Sarvam's education product portfolio, owning end-to-end implementation • Integrate Sarvam's AI models — including speech, language, and multimodal capabilities — into education-focused products • Design and maintain scalable backend services, APIs, and data pipelines that power education applications • Develop responsive, accessible frontend interfaces tailored to diverse learner and educator experiences • Manage the product portfolio lifecycle — from scoping and prioritisation to deployment and iteration • Collaborate closely with product, design, and GTM teams to translate requirements into high-quality builds • Monitor production systems, debug issues, and continuously improve reliability, performance, and user experience • Contribute to technical architecture decisions and help define engineering standards for the education vertical WHAT WE'RE LOOKING FOR • 3–5 years of full stack engineering experience, with a proven track record of shipping production-grade products • Strong proficiency in backend development (Python, Node.js, or equivalent) and frontend frameworks (React, Next.js, or equivalent) • Hands-on experience integrating AI/ML models or APIs into user-facing products • Solid understanding of system design, RESTful APIs, and cloud infrastructure (AWS, GCP, or Azure) • Ability to manage multiple workstreams and product components simultaneously with high attention to detail • Strong product sense — understands user needs and translates them into clean, functional experiences • Clear communicator who collaborates effectively across engineering, product, and business teams BONUS POINTS • Prior experience building products for the education sector or EdTech platforms • Familiarity with speech or NLP technologies, especially in Indian language contexts • Experience with low-bandwidth or mobile-first product design for Tier 2/3 markets WHY SARVAM? Sarvam is a fast-moving, high talent-density team building full-stack AI for India, working on problems that push the frontiers of AI with real population-scale impact. • Work alongside researchers, engineers, builders, and business leaders who move fast and hold each other to a very high bar • High ownership and high impact, from day one • Everything we do is AI-first, from the way we build and ship to the way we think about problems • You can work on problems that could change how an entire country learns, works, and communicates If you want to work on problems at the frontier of AI in India, Sarvam is the place to be.", "summaryDescription" : "Engineering — Full Stack AI Engineer at Sarvam. Skills: Full Stack AI, Backend services, Frontend interfaces, AI model integration. Build and ship full stack features. Integrate AI models", "createdAt" : "2026-06-14T17:42:52.972", "lastUpdated" : "2026-06-15T21:21:41.453", "ingestTimestamp" : "2026-06-14T17:42:52.972", "mongoId" : "6a2c692274d8ee00a09062a3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Full stack engineering", "Backend development", "Frontend development", "API integration", "Data pipelines", "Full Stack AI", "Backend services", "Frontend interfaces", "AI model integration", "System design", "Product sense", "Scoping", "Prioritisation", "Deployment", "Iteration", "Sovereign AI", "Indian AI platform", "Speech capabilities", "Language capabilities", "Multimodal capabilities", "Education sector", "EdTech platforms", "Indian language contexts", "Tier 2/3 markets" ], "skillCount" : 24, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306afff292fd229cfceb63", "title" : "Sr Manager, Distribution Insights and Analytics", "company" : "NBCUniversal", "industry" : "Entertainment", "salary" : { "min" : 120000.0, "max" : 145000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, NEW YORK, United States", "locations" : [ "New York", "NEW YORK", "United States" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T09:18:42.965", "fingerprint" : "afaa085e21ddbf0c4130a3767da4a46bd58a9db2da6ebd7e96afc025017dff0f", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/NBCUniversal3/744000132217389-sr-manager-distribution-insights-and-analytics", "externalId" : "744000132217389", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "SQL, Python, R, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, AWS, GCP, Azure, SageMaker, Vertex AI, Synapse, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, Tableau, Power BI, Looker", "professionalSkills" : [ "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Data engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Data analysis", "Data engineering", "Machine learning", "Business intelligence", "Statistical modeling", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Business intelligence", "level" : "intermediate" }, { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data analytics, Machine learning, Business intelligence, Data engineering", "majorSkillsList" : [ "Data analytics", "Machine learning", "Business intelligence", "Data engineering" ], "coreResponsibilities" : "Develop and maintain data pipelines, Build and optimize data models, Design and implement BI solutions, Perform statistical analysis, Develop and deploy machine learning models, Collaborate with stakeholders to understand data needs, Communicate insights and recommendations, Ensure data quality and integrity", "teamCollaboration" : "Cross-functional teams; Stakeholders", "domainKnowledge" : "Data science; Data engineering; Machine learning; Business intelligence; Analytics engineering; Quantitative analysis; Cloud data stacks; ML frameworks; BI platforms; Statistical methods; Modelling skills", "domainList" : [ "data-science", "data-engineering", "machine-learning", "business-intelligence", "analytics-engineering", "quantitative-analysis", "cloud-data-stacks", "ml-frameworks", "bi-platforms", "statistical-methods", "modelling-skills" ], "domainSpecificKnowledge" : [ "Data science", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "Modelling skills" ], "toolProficiency" : [ "SQL", "Python", "R", "Spark", "Dbt", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "AWS", "GCP", "Azure", "SageMaker", "Vertex AI", "Synapse", "ML Studio", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Communicate insights; Communicate recommendations", "problemSolvingSkills" : "Data analysis; Statistical analysis; Troubleshooting", "qualificationsBasic" : "5+ years of experience in data analytics or related field, Proficiency in SQL, Bachelor's degree in a quantitative field", "qualificationsPreferred" : "Master's degree preferred, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), Experience with BI tools (Tableau, Power BI, Looker)", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "NBCUniversal is one of the world's leading media and entertainment companies. We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our global theme park destinations, consumer products, and experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through our powerhouse film and television studios, including Universal Pictures, DreamWorks Animation, and Focus Features, and the four global television studios under the Universal Studio Group banner, and operate industry-leading theme parks and experiences around the world through Universal Destinations & Experiences, including Universal Orlando Resort, home to Universal Epic Universe, and Universal Studios Hollywood. NBCUniversal is a subsidiary of Comcast Corporation. Visit www.nbcuniversal.com for more information. Our impact is rooted in improving the communities where our employees, customers, and audiences live and work. We have a rich tradition of giving back and ensuring our employees have the opportunity to serve their communities. We champion an inclusive culture and strive to attract and develop a talented workforce to create and deliver a wide range of content reflecting our world. About Platform Distribution & Partnerships: Platform Distribution and Partnerships is a division of NBCUniversal's media group responsible for the distribution and monetization of the company’s multi-billion-dollar linear and streaming services portfolio to pay-tv providers, NBC broadcast affiliates, consumer technology platforms and devices, and consumer brands. A key revenue-generator, the division is comprised of content distribution, affiliate relations and strategic partnerships across NBC, Peacock, Bravo, Telemundo and various FAST channels This is a unique and outstanding opportunity that offers exposure to all aspects of the NBC Network. The Affiliate Relations Division liaises between the NBC Network/Peacock and the 200+ NBC Affiliate Local Stations around the US. This includes working with Entertainment, Sports, News and Peacock. The Sr. Manager will lead the insights and analytics function for the division, focusing on the evolution of consumer viewing habits across linear and streaming platforms. The efforts will inform NBC’s broadcast distribution strategy across partners and platforms. The ideal candidate is a self-starter that can leverage a wide range of data tools to support high-visibility projects. Responsibilities * Responsible for supporting all ratings/data requests (recurring and ad-hoc) for Affiliate Relations team and larger Platform Distribution & Partnerships organization * Leverage data sources to develop internal presentations and client sales materials for critical affiliate deals * Develop frameworks for evaluating viewership of NBC/competitor content across platforms (Pay-TV, over-the-air, FAST) to shape competitive positioning * Work with leadership, communications, PR and other teams to support the development of materials for clients and industry platforms * Represent Affiliate Relations/Broadcast perspective when working on initiatives with vendors (i.e. Nielsen) and broader Decision Sciences organization * Work across NBCU departments to manage platforms and databases housing key station/market information such as ratings and clearances * Support Affiliate Reps in managing daily affiliate station relationships, with a focus on driving operational consistency ## Qualifications Qualifications * 6+ years of experience in insights, strategy, consulting or a related function * 3+ years of experience in measurement, analytics or insights at a media company (station, network, data platform) * Expertise in Media research platforms such as Nielsen, comScore, SNL Kagan, Adobe, Antenna * Expert Excel skills and experience compiling, transforming, and modeling stories using large datasets * Experience crafting compelling PowerPoint presentations that tell meaningful stories with data * Familiarity working with visualization tools (ex. Tableau) * Superior organizational and administrative skills with the ability to multi-task and prioritize work required * Excellent verbal and written communication skills with all levels both internal and external Additional Requirements: * Hybrid: This position currently has a hybrid schedule, which requires contributing from the office a minimum of four days per week. The Company reserves the right to change in-office requirements at any time. * This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. * Sr. Manager Salary range: $120,000 - $145,000 (Bonus Eligible) ## Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to AccessibilitySupport@nbcuni.com.", "summaryDescription" : "Sr Manager, Distribution Insights and Analytics at NBCUniversal. Skills: Data analytics, Machine learning, Business intelligence, Data engineering. Develop and maintain data pipelines. Build and optimize data models", "postedDate" : "2026-06-15T14:25:16.000", "createdAt" : "2026-06-16T00:14:42.954", "lastUpdated" : "2026-06-16T09:18:42.965", "ingestTimestamp" : "2026-06-16T00:14:42.954", "mongoId" : "6a306afff292fd229cfceb63", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 120000, "salaryAnnualMax" : 145000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data analysis", "Data engineering", "Machine learning", "Business intelligence", "Statistical modeling", "A/B testing", "Causal inference", "Data analytics", "Data modeling", "Statistical analysis", "Quantitative analysis", "Data science", "Analytics engineering", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "Modelling skills", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "SQL", "Python", "R", "Spark", "Dbt", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "AWS", "GCP", "Azure", "SageMaker", "Vertex AI", "Synapse", "ML Studio", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "Tableau", "Power BI", "Looker" ], "skillCount" : 52, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Manager", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Media", "llmIndustryConfidence" : 0.95 }, { "id" : "6a304ff3f292fd229ceeb334", "title" : "Sr Manager, Distribution Insights and Analytics", "company" : "NBCUniversal", "industry" : "Entertainment", "salary" : { "min" : 120000.0, "max" : 145000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, NEW YORK, United States", "locations" : [ "New York", "NEW YORK", "United States" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T08:45:12.856", "fingerprint" : "55427dd654eb7d917189288e6c25472957d891875ce5f91427c51d29ab5b8218", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/NBCUniversal3/744000132217389-sr-manager-distribution-insights-and-analytics", "externalId" : "744000132217389", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "SQL, Python, R, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure, SageMaker, Vertex AI, Synapse, ML Studio, Tableau, Power BI, Looker", "professionalSkills" : [ "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Data engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Data analysis", "Data modeling", "Statistical methods", "Machine learning", "Data engineering", "Business intelligence", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "Business intelligence", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data Science, Data Engineering, Machine Learning, Business Intelligence", "majorSkillsList" : [ "Data Science", "Data Engineering", "Machine Learning", "Business Intelligence" ], "coreResponsibilities" : "Develop and maintain data pipelines, Build and deploy machine learning models, Create and manage BI dashboards, Perform data analysis and generate insights, Collaborate with stakeholders to understand data needs, Ensure data quality and integrity, Stay current with industry trends and technologies", "teamCollaboration" : "Cross-functional teams; Stakeholders", "domainKnowledge" : "Data warehousing; Cloud data stacks; ML frameworks; BI platforms; Statistical modelling", "domainList" : [ "data-warehousing", "cloud-data-stacks", "ml-frameworks", "bi-platforms", "statistical-modelling" ], "domainSpecificKnowledge" : [ "Data warehousing", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical modelling" ], "toolProficiency" : [ "SQL", "Python", "R", "Spark", "Dbt", "Snowflake", "BigQuery", "Redshift", "Databricks", "Airflow", "Tableau", "Power BI", "Looker", "Scikit-learn", "TensorFlow", "PyTorch" ], "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "5+ years of experience in analytics or data science, Proficiency in SQL, Experience with Python or R, Experience with data visualization tools", "qualificationsPreferred" : "Master's degree in a quantitative field, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), Experience with data warehousing solutions (Snowflake, BigQuery, Redshift), Experience with BI platforms (Tableau, Power BI, Looker)", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "NBCUniversal is one of the world's leading media and entertainment companies. We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our global theme park destinations, consumer products, and experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through our powerhouse film and television studios, including Universal Pictures, DreamWorks Animation, and Focus Features, and the four global television studios under the Universal Studio Group banner, and operate industry-leading theme parks and experiences around the world through Universal Destinations & Experiences, including Universal Orlando Resort, home to Universal Epic Universe, and Universal Studios Hollywood. NBCUniversal is a subsidiary of Comcast Corporation. Visit www.nbcuniversal.com for more information. Our impact is rooted in improving the communities where our employees, customers, and audiences live and work. We have a rich tradition of giving back and ensuring our employees have the opportunity to serve their communities. We champion an inclusive culture and strive to attract and develop a talented workforce to create and deliver a wide range of content reflecting our world. About Platform Distribution & Partnerships: Platform Distribution and Partnerships is a division of NBCUniversal's media group responsible for the distribution and monetization of the company’s multi-billion-dollar linear and streaming services portfolio to pay-tv providers, NBC broadcast affiliates, consumer technology platforms and devices, and consumer brands. A key revenue-generator, the division is comprised of content distribution, affiliate relations and strategic partnerships across NBC, Peacock, Bravo, Telemundo and various FAST channels This is a unique and outstanding opportunity that offers exposure to all aspects of the NBC Network. The Affiliate Relations Division liaises between the NBC Network/Peacock and the 200+ NBC Affiliate Local Stations around the US. This includes working with Entertainment, Sports, News and Peacock. The Sr. Manager will lead the insights and analytics function for the division, focusing on the evolution of consumer viewing habits across linear and streaming platforms. The efforts will inform NBC’s broadcast distribution strategy across partners and platforms. The ideal candidate is a self-starter that can leverage a wide range of data tools to support high-visibility projects. Responsibilities * Responsible for supporting all ratings/data requests (recurring and ad-hoc) for Affiliate Relations team and larger Platform Distribution & Partnerships organization * Leverage data sources to develop internal presentations and client sales materials for critical affiliate deals * Develop frameworks for evaluating viewership of NBC/competitor content across platforms (Pay-TV, over-the-air, FAST) to shape competitive positioning * Work with leadership, communications, PR and other teams to support the development of materials for clients and industry platforms * Represent Affiliate Relations/Broadcast perspective when working on initiatives with vendors (i.e. Nielsen) and broader Decision Sciences organization * Work across NBCU departments to manage platforms and databases housing key station/market information such as ratings and clearances * Support Affiliate Reps in managing daily affiliate station relationships, with a focus on driving operational consistency ## Qualifications Qualifications * 6+ years of experience in insights, strategy, consulting or a related function * 3+ years of experience in measurement, analytics or insights at a media company (station, network, data platform) * Expertise in Media research platforms such as Nielsen, comScore, SNL Kagan, Adobe, Antenna * Expert Excel skills and experience compiling, transforming, and modeling stories using large datasets * Experience crafting compelling PowerPoint presentations that tell meaningful stories with data * Familiarity working with visualization tools (ex. Tableau) * Superior organizational and administrative skills with the ability to multi-task and prioritize work required * Excellent verbal and written communication skills with all levels both internal and external Additional Requirements: * Hybrid: This position currently has a hybrid schedule, which requires contributing from the office a minimum of four days per week. The Company reserves the right to change in-office requirements at any time. * This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. * Sr. Manager Salary range: $120,000 - $145,000 (Bonus Eligible) ## Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to AccessibilitySupport@nbcuni.com.", "summaryDescription" : "Sr Manager, Distribution Insights and Analytics at NBCUniversal. Skills: Data Science, Data Engineering, Machine Learning, Business Intelligence. Develop and maintain data pipelines. Build and deploy machine learning models", "postedDate" : "2026-06-15T14:25:16.000", "createdAt" : "2026-06-15T21:41:18.491", "lastUpdated" : "2026-06-16T08:45:12.856", "ingestTimestamp" : "2026-06-15T21:41:18.491", "mongoId" : "6a304ff3f292fd229ceeb334", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 120000, "salaryAnnualMax" : 145000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data analysis", "Data modeling", "Statistical methods", "Machine learning", "Data engineering", "Business intelligence", "A/B testing", "Causal inference", "Data Science", "Data Engineering", "Machine Learning", "Business Intelligence", "Statistical analysis", "Quantitative analysis", "Data warehousing", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical modelling", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "SQL", "Python", "R", "Spark", "Dbt", "Snowflake", "BigQuery", "Redshift", "Databricks", "Airflow", "Tableau", "Power BI", "Looker", "Scikit-learn", "TensorFlow", "PyTorch" ], "skillCount" : 39, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Manager", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Media", "llmIndustryConfidence" : 0.95 } ], "status" : 200, "message" : "ai data engineer ringlink customer service engineering and insights jobs", "metadata" : { "title" : "ai data engineer ringlink customer service engineering and insights" }, "pagination" : { "page" : 0, "limit" : 50, "totalCount" : 152334, "totalPages" : 3047, "hasNext" : true, "hasPrevious" : false } }

Remote Ai Data Engineer Ringlink Customer Service Engineering And Insights Jobs

Top Skills

Director, Data and AI Engineering

Director, Data and AI Engineering

Software Engineer, Customer Insights

Software Engineer - Customer Insights

Director Engineering, AI & Data

Data Engineering Manager, Planning and Audience Insights

Data Engineer, WW Promotions Data and Insights

Data Engineer, Sales Insights, Analytics, Data Engineering and Science (SIADS)

AI and Data Engineer, Google Cloud

Director, Customer Success Data Engineering

Director, Customer Success Data Engineering

Data & AI Engineer

Data and AI Consultant

Strategy and Insights Manager, Large Customer Sales

Evidence and Insights Manager

Director, Insights and Analytics

AI & AWS Software Development Engineer, Ringlink CS Technology Enablement

Engineering Lead - Insurance (Data & AI)

Sr. Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements

Senior AI Engineer, Product Engineering

Retail Data & Consumer Insights Intern

Business Intelligence Engineer, P2 Science, Data, and Insights

Sr/Lead AI Backend Data Engineering - GenAI

Senior AI Data Engineer

Sr. Prototyping Architect, AWS Prototyping and AI Customer Engineering (PACE)

AI Engineering Lead

Senior Product Manager, Customer Insights

Senior Product Manager, Customer Insights

Senior Software Engineer - Data Engineering

Lead Product Manager, Data and AI

Principal Software Engineer, Data Engineering

Business Intelligence Engineer, P2 Science, Data, and Insights

SDE-II, AI Core Infra - AI Analytics and Insights

Senior Data Scientist, Product, AI Context Engineering

T6_Chief Data and AI Architect

Senior Data and Analytics Engineer

Lead Product Manager, Data and AI

Data and AI Marketing Intern

Customer Engineering Director

Customer Engineering Director

Sr Director, Data and Application Engineering

AI-Enabled Data Engineer

Sr Director Analyst - AI and Software Engineering

Quality and Insights Manager

Customer Service and Sales Representative - Seasonal

Senior Data & AI Engineer

Sr. Manager, Customer Performance & Insights

Engineering — Full Stack AI Engineer

Sr Manager, Distribution Insights and Analytics

Sr Manager, Distribution Insights and Analytics

Related Searches

All Ai Data Engineer Ringlink Customer Service Engineering And Insights Jobs by City

More Remote Jobs

Common Questions