{ "count" : 37835, "data" : [ { "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. 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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" : "6a3066fff292fd229cfb805a", "title" : "Manager, International Data and Strategy", "company" : "The National Football League", "industry" : "Sports & Fitness", "salary" : { "min" : 125000.0, "max" : 160000.0, "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" : "2026-06-16T11:06:39.308", "fingerprint" : "e94f06cfdc68def5c408265f1856d6fe9ae9b66f2e39878d1bcb2aa5fb6e5d61", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/nflcareers/jobs/5263067008", "externalId" : "5263067008", "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", "minimumEducation" : "Master's", "experienceMinYears" : 5, "experienceLevel" : "Manager", "technicalSkills" : "AWS Redshift, Adobe Marketing Suite, AEP, AEM, AJO, Power BI, Tableau", "professionalSkills" : [ "Data strategy", "Product ownership", "Technical leadership" ], "hardSkillsList" : [ "Data governance", "Data lakes", "Cloud data platforms", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Leadership", "Influencing" ], "hardSkills" : [ { "name" : "Data governance", "level" : "intermediate" }, { "name" : "Data lakes", "level" : "intermediate" }, { "name" : "Cloud data platforms", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Influencing" } ], "majorSkills" : "Data strategy, Product ownership, Technical leadership", "majorSkillsList" : [ "Data strategy", "Product ownership", "Technical leadership" ], "coreResponsibilities" : "Develop data strategy, Own product roadmaps, Lead technical initiatives, Manage enterprise-scale data initiatives, Oversee cloud data platforms, Oversee data lakes, Oversee governance frameworks, Ensure privacy and compliance, Manage consent data, Engage senior leaders, Work with technical partners, Motivate teams", "teamCollaboration" : "Cross-functional teams; Matrixed organization", "domainKnowledge" : "Fan engagement; Lifecycle marketing", "domainList" : [ "fan-engagement", "lifecycle-marketing" ], "domainSpecificKnowledge" : [ "Fan engagement", "Lifecycle marketing" ], "toolProficiency" : [ "AWS Redshift", "Adobe Marketing Suite", "Power BI", "Tableau" ], "communicationSkills" : "Senior leader engagement; Technical partner communication", "specialRequirements" : "No relocation assistance", "qualificationsBasic" : "5+ years in data strategy, 5+ years in product ownership, 5+ years in technical leadership, Master’s degree or higher, SQL proficiency, 5+ years of experience", "qualificationsPreferred" : "Advanced degree preferred, Experience with privacy and compliance standards, Experience with GDPR/CCPA, Experience with consent data management, Knowledge of sports or fan-focused businesses, Understanding of fan engagement, Understanding of lifecycle marketing, Experience with AWS Redshift, Experience with Adobe Marketing Suite, Experience with AEP, Experience with AEM, Experience with AJO, Experience with Power BI, Experience with Tableau, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking a highly motivated Manager, International Data advanced degree preferred. 5+ years in data strategy, product ownership, or technical leadership roles. Exposure to enterprise-scale data initiatives, including cloud data platforms, data lakes, and governance frameworks. Experience with privacy and compliance standards, including GDPR/CCPA and consent data management, is preferred. Knowledge of sports or fan-focused businesses, including an understanding of fan engagement and lifecycle marketing, is an advantage. Proven experience working with AWS Redshift, Adobe Marketing Suite (AEP, AEM, AJO), BI Tools like Power BI, Tableau in a production environment is a plus. Demonstrated track record of collaborating across cross-functional teams and influencing decisions in a matrixed organization without direct reporting authority. Excellent communication skills with a demonstrated ability to engage senior leaders, work effectively with technical partners, and motivate teams to achieve high performance. Other Key Attributes / Characteristics Master’s degree or higher in statistics, data science, computer science, or other data related fields Terms / Expected Hours of Work Limited Travel Salary / Pay Range This job posting contains a pay range, which represents the range of salaries or hourly rates that the NFL believes, in good faith, at the time of this posting that it might be willing to pay for the posted job in the location(s) specified. The NFL expects to hire for this position near the middle of the range. Only in truly rare and exceptional circumstances, where an external candidate has experience, credentials or expertise that far exceed those required or expected for the position, would the NFL consider paying a salary or rate near the higher end of the range. Salary $125,000—$160,000 USD Benefits Information To learn more about our comprehensive benefits offerings, please visit: NFL BENEFITS At the NFL, in-person work at our offices is a top priority because it allows us to collaborate more effectively, build stronger connections, and maintain the culture that drives our success. This role requires onsite presence at an NFL office or stadium location, and remote and/or hybrid working options are not offered. NO RELOCATION ASSISTANCE WILL BE PROVIDED. The NFL is committed to building an inclusive work environment that reflects our incredible fan base. We provide an environment of mutual respect where equal employment opportunities are available to all employees and applicants without regard to status as protected by applicable federal, state, and local laws. WHO WE ARE: NFL Core Values: Respect: Everyone matters. We celebrate diverse opinions, honor hard work, and value every contribution. Integrity: We do what's right, even when it's tough. We hold ourselves accountable and always follow through. Team Responsibility: We support each other and our communities. No one is bigger than the game, and every action impacts others. Resiliency: We set high standards, overcome adversity, and adapt to challenges, always striving for excellence. NFL Leadership Attributes: Build Talent: We develop and nurture potential, empowering individuals to grow and succeed. Execute: We take action with precision, delivering results that drive our goals forward. Inspire: We motivate others through vision, energy, and a commitment to excellence. Live Our Values: We embody our core principles in every decision and action. Know the Business: We stay informed, understand our industry, and make decisions that strengthen our position. Think Big: We challenge the status quo, envision bold possibilities, and strive for transformative impact WHO YOU ARE: Talent Attributes: What we expect for our employees: Embody an enthusiastic, proactive can-do attitude Embrace grit, free from ego or entitlement Excel as a relationship builder, with the ability to influence Eager learner, driven by passion rather than just ambition Encompasses an incredible work ethic with an agile mindset", "summaryDescription" : "Manager, International Data and Strategy at The National Football League. Skills: Data strategy, Product ownership, Technical leadership. Develop data strategy. 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"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. 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"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" : "6a2c957a74d8ee00a098d2de", "title" : "CRM and Data Manager", "company" : "DIM Brands International", "industry" : "Retail", "salary" : { "min" : 65000.0, "max" : 95000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Manager in Retail in Rueil-Malmaison, France, adjusted for seniority and company size." }, "location" : "DIM", "locations" : [ "DIM" ], "timestamp" : "2026-06-15T10:19:28.809", "fingerprint" : "f05a02a872fa9bbf998c777d4bd011e4d6e7f569d770000a0b2c45630039132c", "source" : "greenhouse", "language" : "fr", "applyUrl" : "https://job-boards.greenhouse.io/dim/jobs/8002978", "externalId" : "8002978", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Rueil-Malmaison", "country" : "France", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "48.8777800,2.1802832" } ], "locationText" : "Rueil-Malmaison, France", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "CRM, Data management, Customer Data Platform, IA", "professionalSkills" : [ "Customer engagement", "Customer retention", "Customer satisfaction", "Omnichannel approach", "Data analysis", "Reporting", "Process optimization" ], "hardSkillsList" : [ "Data quality monitoring", "Performance tracking", "KPI reporting", "Customer service management" ], "hardSkills" : [ { "name" : "Data quality monitoring", "level" : "intermediate" }, { "name" : "Performance tracking", "level" : "intermediate" }, { "name" : "KPI reporting", "level" : "intermediate" }, { "name" : "Customer service management", "level" : "intermediate" } ], "majorSkills" : "CRM, Data Management, Customer Experience, Team Leadership", "majorSkillsList" : [ "CRM", "Data Management", "Customer Experience", "Team Leadership" ], "coreResponsibilities" : "Pilot engagement plans, Pilot retention plans, Pilot satisfaction plans, Supervise campaign implementation, Supervise customer journeys, Supervise activation scenarios, Coordinate CRM program redesign, Coordinate CRM program optimization, Ensure targeting relevance, Ensure database exploitation, Monitor data quality, Identify data anomalies, Track performance, Update key dashboards, Report regularly to management, Share best practices, Share campaign results, Manage collaborators daily, Help collaborators upskill, Track collaborator planning, Resolve daily issues, Supervise European customer service, Optimize response processes, Ensure tool configuration", "teamCollaboration" : "IT teams; E-commerce teams; Retail teams; European countries", "domainKnowledge" : "Retail; E-commerce", "domainList" : [ "retail", "e-commerce" ], "domainSpecificKnowledge" : [ "Retail", "E-commerce" ], "toolProficiency" : [ "Klaviyo", "Gladly" ], "innovationCreativity" : "Propose new ideas; Propose new tools", "problemSolvingSkills" : "Identify anomalies; Resolve issues", "outcomesObjectives" : "Measure action impact", "qualificationsBasic" : "8 to 10 years experience, Management experience, Comfortable with numbers, Understand database functioning, Rigorous, Proficient in campaign management tools, Proficient in customer service tools, Fluent English", "qualificationsPreferred" : "Retail or e-commerce experience", "workSiteFlexibility" : "Flexible", "rawDescription" : "DIM Brands International (DBI) est un fabricant et distributeur éco-responsable de sous-vêtements des marques parmi les plus fortes au monde (DIM, Nur Die, Lovable, La Senza...) pour toute la famille. DIM est le leader du marché en France et la marque préférée des consommateurs français (Étude OpinionWay – 1059 répondants – février 2025), Nur Die est le leader du marché en Allemagne dans le segment des produits de consommation, Lovable est un solide second sur le marché italien de la lingerie et La Senza est une marque canadienne emblématique de sous-vêtements. Les produits DIM sont distribués en Omnicanalité (GMS, Ecommerce et Boutiques DIM). Fondée en 1960, DBI a une longue tradition d'innovation et d'excellence. En 2022, l'entreprise a retrouvé son indépendance et entend accélérer sa croissance en s'appuyant sur une stratégie claire basée sur quatre axes : le développement de ses marques phares, un solide programme d'innovations produits, une stratégie omnicanale forte et un programme d'excellence opérationnelle continue. \"Simplification and Scale\" est notre devise stratégique. Notre ambition est d'ouvrir un nouveau cycle de croissance rentable et de réaliser le plein potentiel mondial de la marque DIM. Le siège de DBI est situé à Rueil-Malmaison, près de Paris, avec des filiales dans toute l'Europe (DACH, Italie, Ibérie, Europe de l'Est, Canada) et des distributeurs au Moyen-Orient, en Asie et en Afrique. Son centre d'approvisionnement (fabrication et logistique) est basé à Autun, en Bourgogne, où plus de 5 milliards de collants ont été produits depuis la création de DIM ! De plus, nous sommes profondément engagés dans une stratégie dynamique ESG, structurée autour de 3 piliers : Planète, Produit, Personnes. Par exemple, la marque DIM est neutre en CO2 scope 1&2, grâce à un mix de réduction et de capture des émissions. Dans ce contexte, la direction e-commerce recrute un CRM and Data Manager en CDI. Contexte & Enjeux Sous la responsabilité de la Directrice E-commerce, vous pilotez les plans d'actions d’engagement, de fidélisation et de satisfaction client de nos différentes marques (Dim, Playtex, Abanderado, Lovable….). Le poste est basé en France (siège), d'où vous coordonnez le périmètre européen. À la tête d'une équipe de 2 personnes (un(e) Responsable CRM et un(e) Responsable Service Client), et en étroite collaboration avec les équipes IT, E-commerce et Retail, vous veillez à la cohérence de l'expérience client depuis le premier contact jusqu'au service après-vente. Manager de proximité, vous aimez le travail en équipe et apportez votre soutien opérationnel à vos collaborateurs en maîtrisant les outils du quotidien. Vos Missions Animation & Déploiement CRM / Fidélisation Superviser et accompagner la mise en œuvre opérationnelle des campagnes, des parcours clients (approche omnicanale) et des scénarios d'activation. Coordonner les projets de refonte ou d'optimisation des programmes CRM pour nos marques en Europe, en lien avec les équipes IT, E-commerce et Retail. Garantir la pertinence des ciblages et la bonne exploitation de la base de données clients (Customer Data Platform) en collaboration avec l'IT. Amélioration continue : Assurer une veille sur les bonnes pratiques du marché et proposer de nouvelles idées ou outils simples (nouveaux canaux, IA d'aide à la rédaction, etc.) pour moderniser nos pratiques. Faire évoluer le programme de fidélité de DIM France et optimiser les scénarios d’automation. Suivi des données & Reporting Suivi de la qualité de la donnée : vous comprenez les flux de données pour repérer les anomalies simples (problèmes d'import, écarts de chiffres, bugs outils) et faites le lien avec les équipes IT pour leur résolution. Suivre la performance : Suivre et mettre à jour les dashboards clés (KPIs d'engagement, conversion, rétention, NPS) pour mesurer l'impact des actions. Partage des résultats : Assurer un reporting régulier auprès de la direction et des pays pour partager les bonnes pratiques et les résultats des campagnes. Management, Support Outils & Service Client Manager et accompagner au quotidien vos 2 collaborateurs : vous les aidez à monter en compétences, suivez leur planning et débloquez avec eux les sujets du quotidien sur les outils (Klaviyo, Gladly, etc.). Superviser le Service Client européen (géré opérationnellement par votre collaborateur), en l'aidant à optimiser les process de réponse et à s'assurer du bon paramétrage de l'outil de ticketing. Profil recherché Expérience : 8 à 10 ans d'expérience en CRM, marketing relationnel ou expérience client, idéalement dans l'univers du retail ou du e-commerce. Management & Posture : Vous avez une première expérience de management et un tempérament de \"facilitateur\". Vous aimez être proche de votre équipe et l'aider concrètement sur le terrain. Sensibilité Tech & Data : Vous êtes à l'aise avec les chiffres et comprenez le fonctionnement d'une base de données. Vous êtes rigoureux(se) et savez repérer quand \"un chiffre ne colle pas\" dans un outil. Compétences outils : Vous avez une bonne maîtrise pratique des outils de gestion de campagne (idéalement Klaviyo) et de service client (Gladly ou équivalent). Qualités personnelles : Forte orientation client, rigueur, bon relationnel pour travailler avec des interlocuteurs variés (IT, Retail, pays). Langues : Anglais courant indispensable pour échanger avec nos interlocuteurs internes et prestataires. Le poste est basé à Rueil-Malmaison dans des locaux au bord de la Seine. Life @DIM : Les collaborateurs sont mis au cœur de la stratégie de l’entreprise, ce qui vous permet d'obtenir les avantages suivants : Évoluer au sein d’un environnement stimulant parmi une équipe jeune et dynamique, et relever de nouveaux défis chaque jour Profiter du restaurant d'entreprise Avoir accès aux ventes organisées par le CE et 30% de réduction sur les produits de nos boutiques et sites internet Avoir un accès à la Conciergerie (services proposés par des esthéticiennes, ostéopathes, cordonniers…) Coaching sportif", "summaryDescription" : "CRM and Data Manager at DIM Brands International. Skills: CRM, Data Management, Customer Experience, Team Leadership. Pilot engagement plans. Pilot retention plans", "postedDate" : "2026-06-14T09:40:26.019", "createdAt" : "2026-06-14T09:40:26.019", "lastUpdated" : "2026-06-15T10:19:28.809", "ingestTimestamp" : "2026-06-14T09:40:26.019", "mongoId" : "6a2c957a74d8ee00a098d2de", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Data quality monitoring", "Performance tracking", "KPI reporting", "Customer service management", "CRM", "Data Management", "Customer Experience", "Team Leadership", "Customer engagement", "Customer retention", "Customer satisfaction", "Omnichannel approach", "Data analysis", "Reporting", "Process optimization", "Retail", "E-commerce", "Klaviyo", "Gladly" ], "skillCount" : 19, "jobCategory" : "marketing", "jobSubcategory" : "growth", "seniorityLevel" : "Manager", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Retail", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca51974d8ee00a09b4ac2", "title" : "Director, Data Management and Systems", "company" : "Apogee Therapeutics", "industry" : "Biotech", "salary" : { "min" : 215000.0, "max" : 245000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Remote", "locations" : [ "Remote" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T00:34:50.028", "fingerprint" : "a67a650203974e35a7812b79bd50b8cc4f96c4b227cf574f7ee5ceabd7897932", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/apogeetherapeutics/jobs/5161364007", "externalId" : "5161364007", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 12, "experienceLevel" : "Director", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow", "professionalSkills" : [ "Data management", "Systems management", "Data engineering", "Machine learning", "Business intelligence", "Data analytics", "Quantitative analysis", "Statistical modeling" ], "hardSkillsList" : [ "Data warehousing", "ETL processes", "Data modeling", "Database administration", "Cloud computing", "Statistical analysis", "Machine learning algorithms", "Data visualization", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Database administration", "level" : "intermediate" }, { "name" : "Cloud computing", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine learning algorithms", "level" : "intermediate" }, { "name" : "Data visualization", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data management, Systems management, Machine learning, Business intelligence", "majorSkillsList" : [ "Data management", "Systems management", "Machine learning", "Business intelligence" ], "coreResponsibilities" : "Oversee data management systems, Ensure data integrity, Develop and implement data strategies, Manage data governance policies, Lead data engineering initiatives, Build and maintain data pipelines, Optimize data storage and retrieval, Implement data quality controls, Drive analytics and BI initiatives, Develop predictive models, Collaborate with stakeholders", "teamCollaboration" : "Cross-functional teams; Business stakeholders", "domainKnowledge" : "Genomics; Drug discovery; Clinical trials", "domainList" : [ "genomics", "drug-discovery", "clinical-trials" ], "domainSpecificKnowledge" : [ "Genomics", "Drug discovery", "Clinical trials" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Stakeholder communication", "documentationSkills" : "Technical documentation", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "5+ years experience, SQL proficiency, Bachelor's degree", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Apogee Therapeutics Founded in 2022, Apogee Therapeutics, Inc. (Ticker: APGE) is a well-funded, Nasdaq listed company that offers the opportunity to work in a fast-paced, highly dynamic environment. At Apogee, you can actively contribute to shaping the company culture, take on various roles and responsibilities, and grow professionally. Apogee Therapeutics is a clinical-stage biotechnology company advancing novel biologics with potential for differentiated efficacy and dosing in the largest I ensure accountability and high-quality deliverables. Lead vendor selection and contract input for DM-related services. People Leadership advanced degree preferred. 12+ years of experience in clinical data management within biotech, pharma, or CRO environments. Experience in both operational DM and systems/technology implementation. Demonstrated leadership of DM activities across multiple clinical trials and programs. Technical Expertise Deep knowledge of EDC systems (e.g., Medidata Rave). Strong understanding of CDISC standards (SDTM, CDASH) and data lifecycle. Experience with data integrations, external data (labs, imaging, biomarkers), and decentralized trial technologies. Familiarity with data visualization and analytics tools is a plus. Leadership & Competencies Proven ability to lead cross-functional teams and influence at the program level. Strong strategic thinking with hands-on execution capability. Excellent communication and stakeholder management skills. Experience in fast-paced, growing organizations preferred. Ability to bridge systems/technology with clinical execution. Strong ownership mindset over data quality and delivery timelines. Proactive, solutions-oriented approach to complex data challenges. Effective leadership in ambiguity and evolving clinical landscapes. The anticipated salary range for candidates for this role will be $215,000 - $245,000/year. The final salary offered will depend on several factors, which may include, but is not limited to relevant years of experience, educational background, and geography. What We Offer A great culture, grounded in our C.O.R. E. values: Caring, Original, Resilient and Egoless Opportunity to work in a fast-paced, highly dynamic environment where you help shape the culture and company, wear multiple hats, and learn quickly Market competitive compensation and benefits package, including base salary, performance bonus, equity grant opportunities, health, welfare & retirement benefits We provide competitive time off, including three weeks PTO, two one-week company-wide shutdowns a year and dedicated paid sick leave Commitment to growing you professionally and providing access to resources to further your development Apogee offers regular all team, in-person meetings to build relationships and problem solve E-Verify Participation: As part of the I9 verification of authorization to work in the US, Apogee participates in E-Verify. To learn more about E-Verify please review this poster. Apogee Therapeutics is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. To review our privacy policy, click here 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, Data Management and Systems at Apogee Therapeutics. Skills: Data management, Systems management, Machine learning, Business intelligence. Oversee data management systems. Ensure data integrity", "postedDate" : "2026-06-14T20:07:58.302", "createdAt" : "2026-06-14T20:07:58.302", "lastUpdated" : "2026-06-16T00:34:50.028", "ingestTimestamp" : "2026-06-14T20:07:58.302", "mongoId" : "6a2ca51974d8ee00a09b4ac2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 215000, "salaryAnnualMax" : 245000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Data warehousing", "ETL processes", "Data modeling", "Database administration", "Cloud computing", "Statistical analysis", "Machine learning algorithms", "Data visualization", "A/B testing", "Causal inference", "Data management", "Systems management", "Machine learning", "Business intelligence", "Data engineering", "Data analytics", "Quantitative analysis", "Statistical modeling", "Genomics", "Drug discovery", "Clinical trials", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker" ], "skillCount" : 28, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3087a4f292fd229c08b1f8", "title" : "Business Analyst, Data Masking and Compliance", "company" : "Capco", "industry" : "Consulting", "salary" : { "min" : 118000.0, "max" : 152000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Canada - Toronto", "locations" : [ "Canada - Toronto" ], "timestamp" : "2026-06-16T12:32:44.174", "fingerprint" : "f519232f48132c719665d37d19932956dfa1532fec2df391bf8a340f99776803", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/capco/jobs/8003346", "externalId" : "8003346", "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", "professionalSkills" : [ "Data governance", "Risk remediation", "Stakeholder management", "Data analysis", "Process design", "Process engineering", "Operational improvement" ], "hardSkillsList" : [ "Data masking standards", "Evidence collection", "Compliance reporting", "Governance metrics" ], "hardSkills" : [ { "name" : "Data masking standards", "level" : "intermediate" }, { "name" : "Evidence collection", "level" : "intermediate" }, { "name" : "Compliance reporting", "level" : "intermediate" }, { "name" : "Governance metrics", "level" : "intermediate" } ], "majorSkills" : "Data masking, Compliance, Risk remediation, Data governance", "majorSkillsList" : [ "Data masking", "Compliance", "Risk remediation", "Data governance" ], "coreResponsibilities" : "Assess applications against data masking standards, Identify compliance gaps, Identify remediation requirements, Partner with application owners, Understand application processes, Understand data flows, Understand masking requirements, Design evidence collection processes, Implement evidence collection processes, Demonstrate compliance through objective testing, Facilitate stakeholder discussions, Align business requirements with standards, Support adoption of required controls, Create compliance reporting, Track status, Generate governance metrics", "teamCollaboration" : "Partnering with stakeholders; Bridging business and technology teams; Application owners; Business stakeholders; Senior stakeholders", "projectManagementSkills" : [ "Audit remediation" ], "domainKnowledge" : "Data masking; Data governance; Banking; Payments; Enterprise technology; Risk management; Operational risk", "domainList" : [ "data-masking", "data-governance", "banking", "payments", "enterprise-technology", "risk-management", "operational-risk" ], "domainSpecificKnowledge" : [ "Data masking", "Data governance", "Banking", "Payments", "Enterprise technology", "Risk management", "Operational risk" ], "communicationSkills" : "Stakeholder communication", "continuousLearning" : "Professional development; Industry-leading expertise", "problemSolvingSkills" : "Translating standards; Practical requirements", "outcomesObjectives" : "Strengthen data governance practices; Contribute to risk remediation program", "qualificationsBasic" : "Experience delivering risk, compliance, audit remediation, data governance, or regulatory change initiatives within financial services, Stakeholder management and communication skills, Ability to understand business processes, Experience performing data analysis, Process design, process engineering, or operational improvement experience", "qualificationsPreferred" : "Experience with data masking, Experience with data protection, Experience with privacy controls, Experience with information security programs, Knowledge of banking, Knowledge of payments, Knowledge of enterprise technology environments, Familiarity with audit remediation programs, Familiarity with regulatory examinations, Familiarity with control testing frameworks, Experience designing governance reporting, Experience designing compliance dashboards, Experience designing executive-level status reporting, Understanding of risk management frameworks, Understanding of operational risk practices", "rawDescription" : "Drive Enterprise Risk Remediation Through Data Governance Excellence The Role Capco is seeking a Business Analyst, Data Masking and Compliance to support a critical enterprise audit remediation initiative within a leading financial institution. This newly created role will focus on assessing application compliance against enterprise data masking standards, partnering with stakeholders to drive adoption, and establishing sustainable evidence collection and reporting processes. You will play a key role in bridging business and technology teams, helping application owners understand compliance requirements while ensuring regulatory and audit expectations are met. This is an opportunity to influence enterprise-wide controls, strengthen data governance practices, and contribute to a high-profile risk remediation program. What You’ll Do Assess and prioritize applications requiring review against enterprise data masking standards, identifying compliance gaps and remediation requirements. Partner with application owners and business stakeholders to understand application processes, data flows, and masking requirements. Design and implement evidence collection and validation processes that demonstrate compliance through objective testing rather than attestation alone. Facilitate stakeholder discussions to align business requirements with enterprise standards while supporting adoption of required controls. Create compliance reporting, status tracking, and governance metrics that integrate with broader audit remediation KRIs and KPIs. What We’re Looking For Experience delivering risk, compliance, audit remediation, data governance, or regulatory change initiatives within financial services. Strong stakeholder management and communication skills with the ability to build trust, influence outcomes, and navigate competing priorities. Ability to understand business processes and translate enterprise standards into practical application-level requirements. Experience performing data analysis and interpreting data flows, controls, and compliance requirements. Process design, process engineering, or operational improvement experience with a focus on scalable control frameworks. Bonus Points For Experience with data masking, data protection, privacy controls, or information security programs. Knowledge of banking, payments, and enterprise technology environments. Familiarity with audit remediation programs, regulatory examinations, or control testing frameworks. Experience designing governance reporting, compliance dashboards, and executive-level status reporting. Understanding of risk management frameworks and operational risk practices within large financial institutions. Why Join Capco Work on high-impact regulatory and risk transformation initiatives for leading financial institutions. Partner with senior stakeholders across business, technology, risk, and compliance functions. Join a collaborative, entrepreneurial consulting culture that values innovation and practical problem-solving. Access continuous learning, professional development, and industry-leading expertise. Help shape the future of data governance, compliance, and risk management within the financial services industry. Benefits Comprehensive Benefits Coverage – 100% company-paid health, life, and disability insurance effective from Day 1 of employment. Retirement Savings Program – RRSP with the option of receiving a matching employer contribution. Virtual Health Care and Employee & Family Assistance Program available to employees and their dependents. Enhanced parental leave benefits from Day 1 of employment, plus a company-sponsored new parent gift. Wellness reimbursement and a dedicated Business Coach from Day 1 to support your career growth and development. Why This Role Is Open We are currently hiring for this role due to an existing or newly created vacancy within our organization. This position is open as part of our ongoing business needs, and we are actively reviewing applications to fill this role with a qualified candidate who can make an immediate impact. Inclusion at Capco We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day. Use of Artificial Intelligence in Talent Acquisition At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination. AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams. Pay Transparency The salary range for this position is listed below. Additionally, this position may also be eligible to receive an annual discretionary/variable bonus payment. Capco is committed to providing fair and equitable compensation to our people. Our compensation policies and salary ranges are designed to allow our people to progress through the salary range as they demonstrate strong performance and develop in their role over time. The base pay offered to selected candidates will be within the salary range and the placement will vary based upon a variety of factors, including, but not limited to job-related knowledge, skills, experience and internal equity. Canada Pay Transparency $118,000—$152,000 CAD", "summaryDescription" : "Business Analyst, Data Masking and Compliance at Capco. Skills: Data masking, Compliance, Risk remediation, Data governance. Assess applications against data masking standards. Identify compliance gaps", "postedDate" : "2026-06-16T01:20:47.212", "createdAt" : "2026-06-16T01:20:47.212", "lastUpdated" : "2026-06-16T12:32:44.174", "ingestTimestamp" : "2026-06-16T01:20:47.212", "mongoId" : "6a3087a4f292fd229c08b1f8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data masking standards", "Evidence collection", "Compliance reporting", "Governance metrics", "Data masking", "Compliance", "Risk remediation", "Data governance", "Stakeholder management", "Data analysis", "Process design", "Process engineering", "Operational improvement", "Audit remediation", "Banking", "Payments", "Enterprise technology", "Risk management", "Operational risk" ], "skillCount" : 19, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2cb0de74d8ee00a09db551", "title" : "Senior Data and Platform Engineer", "company" : "Avantos", "industry" : "Engineering", "salary" : { "min" : 165000.0, "max" : 225000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "The estimation is based on 2024-2025 market data for a Senior Data and Platform Engineer in New York, United States, with adjustments for seniority, company size, and the FinTech industry." }, "location" : "New York City", "locations" : [ "New York City" ], "timestamp" : "2026-06-16T01:43:36.688", "fingerprint" : "791ee05e9a932c88a1a3dc229ccc6d96b88ddb4135d2238f2514febf83289574", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/avantos/4b2dc531-155c-4d8a-97b7-d89e27a59c12/application", "externalId" : "4b2dc531-155c-4d8a-97b7-d89e27a59c12", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "40.7127281,-74.0060152" }, { "country" : "United States", "continent" : "na", "workMode" : "remote" }, { "country" : "Canada", "continent" : "na", "workMode" : "remote" } ], "locationText" : "New York, New York, United States; United States; Canada", "employmentType" : "FULL_TIME", "experienceMinYears" : 7, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Golang, SQL, Terraform, AWS, Python, Docker, Kubernetes, LLMs, RAG, Vector search", "professionalSkills" : [ "Backend system design", "API design", "Data modeling", "System design" ], "hardSkillsList" : [ "Data engineering", "Platform engineering", "Backend infrastructure" ], "hardSkills" : [ { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "Platform engineering", "level" : "intermediate" }, { "name" : "Backend infrastructure", "level" : "intermediate" } ], "majorSkills" : "Data platform, AI systems, Infrastructure", "majorSkillsList" : [ "Data platform", "AI systems", "Infrastructure" ], "coreResponsibilities" : "Design backend systems, Implement backend systems, Design data platform, Build data platform, Create scalable systems, Design data models, Design APIs, Make decisions about schemas, Make decisions about indexes, Make decisions about migrations, Make decisions about performance, Own infrastructure for data workloads, Own infrastructure for AI workloads, Enable self-serve data workflows, Improve observability, Improve reliability, Improve performance, Support AI/ML systems, Build tooling for document processing, Build tooling for metadata, Build tooling for normalization", "teamCollaboration" : "Engineering teams; Product teams", "domainKnowledge" : "Fintech; Regulated systems", "domainList" : [ "fintech", "regulated-systems" ], "domainSpecificKnowledge" : [ "Fintech", "Regulated systems" ], "toolProficiency" : [ "Terraform", "AWS", "Docker", "Kubernetes" ], "problemSolvingSkills" : "Performance; Reliability; Failure modes", "specialRequirements" : "Startup environment", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "SENIOR DATA & PLATFORM ENGINEER \uD83D\uDCCD NYC (HYBRID) OR US REMOTE | COMPETITIVE + EQUITY ABOUT AVANTOS Avantos is building the AI-native operating system for financial services — transforming fragmented data into a single, intelligent system that powers workflows, automation, and decision-making. We’re a product-led, fast-moving team at the intersection of AI, fintech, and modern infrastructure. THE ROLE We’re looking for a Senior Data & Platform Engineer to build the data and core platform and infrastructure layer that powers our AI systems. This is not just about pipelines — it’s about creating the systems, tooling, and abstractions that enable engineers and AI workflows to move fast, safely, and reliably. WHAT YOU’LL DO - Design and implement core backend systems and integrations that power the product. - Design and build our data platform (orchestration, pipelines, developer workflows) - Create scalable systems for data ingestion, transformation, and access - Design data models and APIs that won’t collapse under growth. - Make sane decisions about schemas, indexes, migrations, and performance. - Own infrastructure for data + AI workloads (containers, orchestration, cloud services) - Enable self-serve data workflows for engineering and product teams - Improve observability, reliability, and performance across the data stack - Support AI/ML systems (embeddings, vector data, model pipelines) - Build tooling for document processing, metadata, and normalization WHAT WE’RE LOOKING FOR - 7+ years in data engineering, platform engineering, or backend infrastructure - A track record of shipping and owning production systems. - Strong systems thinking (not just pipelines — platform mindset) - Backend system design and API design - Data modeling and relational databases - Performance, reliability, and failure modes - Proficiency in Golang, SQL, Terraform, AWS - Comfort in a fast-moving startup environment BONUS - LLMs / RAG, vector search, fintech or regulated systems - Have startup or early-stage experience. WHY JOIN - Build the foundation layer of an AI-native product - High ownership + direct impact - Work where data, platform, and AI converge THE FIT You’re someone who doesn’t just move data — you build the systems that make data usable at scale.", "summaryDescription" : "Senior Data and Platform Engineer at Avantos. Skills: Data platform, AI systems, Infrastructure. Design backend systems. 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Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve. Our Commitment As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day. Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees. United States-Minnesota-Saint Louis Park", "summaryDescription" : "Utility Data and Modeling Analyst at HDR. Skills: Data analysis, Data modeling. Handle confidential information. Prioritize and handle multiple tasks", "createdAt" : "2026-06-14T21:31:19.547", "lastUpdated" : "2026-06-16T02:46:45.498", "ingestTimestamp" : "2026-06-14T21:31:19.547", "mongoId" : "6a16291c58b93c861e95a08c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 85000, "salaryAnnualMax" : 115000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Data modeling", "Data analysis", "Data engineering", "Business intelligence", "Data science", "Organizational skills", "Utility data", "MS Office", "Power BI", "Tableau" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustryConfidence" : 0.92 }, { "id" : "6a3059d3f292fd229cf4b2e9", "title" : "Program Manager, Foundations Data and Operations", "company" : "OpenAI", "industry" : "Research", "salary" : { "min" : 162000.0, "max" : 240000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-16T08:36:35.216", "fingerprint" : "b5c332c6dff17e08ec57719085edffc2e13874ec8bad2f42503c2cc63f81fd86", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/openai/73c24685-3508-489d-aa92-203761e79f19/application", "externalId" : "73c24685-3508-489d-aa92-203761e79f19", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.6534817,-79.3839347" }, { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "Toronto, Ontario, Canada; San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceLevel" : "Manager", "remoteFriendly" : true, "rawDescription" : "ABOUT THE TEAM The Foundations Data and Operations team is responsible for acquiring the data OpenAI needs to build frontier AI models. We run high-impact data acquisition programs, such as our web crawler and our data partnerships, and work closely with research to build the training datasets for our models. Our work advances the intelligence of our models and teaches them new skills that hundreds of millions of people benefit from every day. ABOUT THE ROLE We are hiring a Program Manager to join our team. In this role, you will lead programs to acquire training data to advance our research roadmap. You will work with researchers to define requirements, design and manage acquisition workflows, and establish processes to execute them at scale. This role requires a blend of strategic thinking and hands-on execution. The ideal candidate can navigate ambiguity, break down complex problems, manage cross-functional stakeholders, and drive alignment across technical and business teams. This role may require living close to some physical operations across the US and some hybrid travel to San Francisco. IN THIS ROLE, YOU WILL: - Work closely with research to understand data needs and define acquisition priorities and timeline that are aligned with our research roadmap. - Translate research objectives into clear technical requirements and operational plans, ensuring data workflows, timelines, and quality standards are executed to the highest quality standards. - Lead vendor and partner engagements for data sourcing – including evaluating suppliers, negotiating agreements, and managing delivery. - Establish and maintain metrics for data quality, throughput, efficiency, and overall program performance, ensuring visibility to leadership and cross-functional partners. - Identify gaps in our data ecosystem and proactively drive initiatives to strengthen our data acquisition and creation capabilities over time. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have 8+ years of experience in operations, strategy, venture capital, private equity, or consulting, with at least 5 years operating within a company. We will also consider high-trajectory candidates with fewer years of experience but at top companies with a clear track record of excellence. - Have experience taking end-to-end ownership of large, ambiguous problems, and breaking them down into clear, actionable plans. - Have direct experience engaging with executives and senior leaders to influence and drive strategic decisions. - Excel under pressure, bringing a high motor and exceptional adaptability and flexibility in a fast-paced, dynamic environment. - Are highly analytical - sophisticated in your understanding and approach to analyses; ability to ask and answer the most important questions, and present results clearly to leaders to influence decision making. - Are comfortable operating at all altitudes – discussing strategy and vision with executives, and troubleshooting operations with individual contributors and external partners. - Have excellent communication and cross-functional collaboration skills. - Are passionate about technology and artificial intelligence, and interested in its impact on business and society. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.", "summaryDescription" : "Program Manager, Foundations Data and Operations at OpenAI", "createdAt" : "2026-06-16T00:28:18.616", "lastUpdated" : "2026-06-16T08:36:35.216", "ingestTimestamp" : "2026-06-16T00:28:18.616", "mongoId" : "6a3059d3f292fd229cf4b2e9", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 162000, "salaryAnnualMax" : 240000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305f0bf292fd229cf77aa8", "title" : "Program Manager, Foundations Data and Operations", "company" : "OpenAI", "industry" : "Research", "salary" : { "min" : 162000.0, "max" : 240000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-16T10:03:10.589", "fingerprint" : "e8731ede0ca67f1d57b4836bee5734cd93890c04bfedb9ec44ddeed31dfc3765", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/OpenAI/73c24685-3508-489d-aa92-203761e79f19/application", "externalId" : "73c24685-3508-489d-aa92-203761e79f19", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.6534817,-79.3839347" }, { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "Toronto, Ontario, Canada; San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceLevel" : "Manager", "remoteFriendly" : true, "rawDescription" : "ABOUT THE TEAM The Foundations Data and Operations team is responsible for acquiring the data OpenAI needs to build frontier AI models. We run high-impact data acquisition programs, such as our web crawler and our data partnerships, and work closely with research to build the training datasets for our models. Our work advances the intelligence of our models and teaches them new skills that hundreds of millions of people benefit from every day. ABOUT THE ROLE We are hiring a Program Manager to join our team. In this role, you will lead programs to acquire training data to advance our research roadmap. You will work with researchers to define requirements, design and manage acquisition workflows, and establish processes to execute them at scale. This role requires a blend of strategic thinking and hands-on execution. The ideal candidate can navigate ambiguity, break down complex problems, manage cross-functional stakeholders, and drive alignment across technical and business teams. This role may require living close to some physical operations across the US and some hybrid travel to San Francisco. IN THIS ROLE, YOU WILL: - Work closely with research to understand data needs and define acquisition priorities and timeline that are aligned with our research roadmap. - Translate research objectives into clear technical requirements and operational plans, ensuring data workflows, timelines, and quality standards are executed to the highest quality standards. - Lead vendor and partner engagements for data sourcing – including evaluating suppliers, negotiating agreements, and managing delivery. - Establish and maintain metrics for data quality, throughput, efficiency, and overall program performance, ensuring visibility to leadership and cross-functional partners. - Identify gaps in our data ecosystem and proactively drive initiatives to strengthen our data acquisition and creation capabilities over time. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have 8+ years of experience in operations, strategy, venture capital, private equity, or consulting, with at least 5 years operating within a company. We will also consider high-trajectory candidates with fewer years of experience but at top companies with a clear track record of excellence. - Have experience taking end-to-end ownership of large, ambiguous problems, and breaking them down into clear, actionable plans. - Have direct experience engaging with executives and senior leaders to influence and drive strategic decisions. - Excel under pressure, bringing a high motor and exceptional adaptability and flexibility in a fast-paced, dynamic environment. - Are highly analytical - sophisticated in your understanding and approach to analyses; ability to ask and answer the most important questions, and present results clearly to leaders to influence decision making. - Are comfortable operating at all altitudes – discussing strategy and vision with executives, and troubleshooting operations with individual contributors and external partners. - Have excellent communication and cross-functional collaboration skills. - Are passionate about technology and artificial intelligence, and interested in its impact on business and society. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.", "summaryDescription" : "Program Manager, Foundations Data and Operations at OpenAI", "createdAt" : "2026-06-16T00:27:48.493", "lastUpdated" : "2026-06-16T10:03:10.589", "ingestTimestamp" : "2026-06-16T00:27:48.493", "mongoId" : "6a305f0bf292fd229cf77aa8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 162000, "salaryAnnualMax" : 240000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "69cf3f062beec4dd3d9340ff", "title" : "Data and Analytics Architect", "company" : "ADCI HYD", "industry" : "Operations, IT, Support Engineering, Solution Architect, Cloud Computing", "salary" : { "min" : 2500000.0, "max" : 4000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Data and Analytics Architect in Hyderabad, India, adjusted for the FinTech industry and company size." }, "location" : "Hyderabad, Telangana, IND", "locations" : [ "Hyderabad, Telangana, IND" ], "timestamp" : "2026-06-15T07:27:32.772", "fingerprint" : "5ad498afe6ceb25c77afff66f9b663db573be509c4597dad8763d7801ca5c8cb", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10382143/apply", "externalId" : "fe65d693-5feb-466a-8c26-5393f1ddf5b6", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hyderabad", "state" : "Telangana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "17.3605890,78.4740613" } ], "locationText" : "Hyderabad, Telangana, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 6, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AWS, Redshift, S3, AWS Glue, Amazon Athena, Amazon QuickSight, AWS Lambda, EMR, Kinesis, FireHose, IAM, SAP", "professionalSkills" : [ "Data engineering", "Analytics architecture", "Data platform design", "Data ingestion", "Data transformation", "Data storage", "Semantic modeling", "Reporting", "Analytics patterns", "Data pipelines", "Data processing", "Reporting architectures", "Data quality", "Data governance", "Data security", "Operational controls", "Business requirements", "Architecture standards", "Data flow diagrams", "Support procedures", "Performance issues", "Data quality concerns", "Corrective actions", "Implementation initiatives", "Migration initiatives", "Modernization initiatives", "Enhancement initiatives", "Platform integration" ], "hardSkillsList" : [ "Data engineering", "Database engineering", "Business intelligence", "Business analytics", "Data warehousing", "Enterprise data platform", "Data pipelines", "Analytics solutions", "Data processing", "Reporting architectures", "Data quality", "Data governance", "Data security", "Operational controls", "Data integration" ], "hardSkills" : [ { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "Database engineering", "level" : "intermediate" }, { "name" : "Business intelligence", "level" : "intermediate" }, { "name" : "Business analytics", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "Enterprise data platform", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Analytics solutions", "level" : "intermediate" }, { "name" : "Data processing", "level" : "intermediate" }, { "name" : "Reporting architectures", "level" : "intermediate" }, { "name" : "Data quality", "level" : "intermediate" }, { "name" : "Data governance", "level" : "intermediate" }, { "name" : "Data security", "level" : "intermediate" }, { "name" : "Operational controls", "level" : "intermediate" }, { "name" : "Data integration", "level" : "intermediate" } ], "majorSkills" : "Data architecture, AWS data services, Data platform design", "majorSkillsList" : [ "Data architecture", "AWS data services", "Data platform design" ], "coreResponsibilities" : "Lead design of data solutions, Lead implementation of data solutions, Lead support of data solutions, Architect data platforms using AWS, Define data ingestion patterns, Implement data ingestion patterns, Define data transformation patterns, Implement data transformation patterns, Define data storage patterns, Implement data storage patterns, Define semantic modeling patterns, Implement semantic modeling patterns, Define reporting patterns, Implement reporting patterns, Define analytics patterns, Implement analytics patterns, Design data pipelines, Optimize data pipelines, Design batch data processing, Optimize batch data processing, Design near real-time processing, Optimize near real-time processing, Design reporting architectures, Optimize reporting architectures, Ensure data quality, Ensure data governance, Ensure data security, Ensure operational controls, Work with business teams, Work with finance teams, Work with IT teams, Work with application teams, Design reliable data solutions, Design scalable data solutions, Develop architecture standards, Maintain architecture standards, Develop design documents, Maintain design documents, Develop data flow diagrams, Maintain data flow diagrams, Develop support procedures, Maintain support procedures, Monitor data pipelines, Monitor analytics platforms, Monitor reporting solutions, Drive corrective actions", "teamCollaboration" : "Business teams; Finance teams; IT teams; Application teams", "domainKnowledge" : "FinTech; SAP data; Finance reporting; Supply chain reporting; Enterprise operational reporting", "domainList" : [ "fintech", "sap-data", "finance-reporting", "supply-chain-reporting", "enterprise-operational-reporting" ], "domainSpecificKnowledge" : [ "FinTech", "SAP data", "Finance reporting", "Supply chain reporting", "Enterprise operational reporting" ], "documentationSkills" : "Design documents; Data flow diagrams", "problemSolvingSkills" : "Problem-solving", "qualificationsBasic" : "6+ years data engineering experience, 8+ years analytics experience, Experience designing scalable data pipelines, Experience designing cloud-based analytics solutions, Excellent analytical skills, Excellent problem-solving skills, Excellent stakeholder management skills, Ability to work independently, Ability to work as part of a team", "qualificationsPreferred" : "Knowledge of SAP data platforms, Experience with real-time data processing, Experience with event-driven data processing, Experience with data lake architecture, Experience with data warehouse architecture, Experience with hybrid analytics architecture, Experience with enterprise reporting, Experience with KPI frameworks, Experience with dashboard design, Knowledge of finance reporting domains, Knowledge of supply chain reporting domains, Knowledge of enterprise operational reporting domains, Experience leading data modernization initiatives, Experience leading cloud transformation initiatives", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking an experienced Data and Analytics Architect to join our team. The ideal candidate will be responsible for leading the design, implementation, and support of scalable data and analytics solutions on AWS, enabling trusted reporting, enterprise insights, and seamless integration across enterprise platforms. The primary focus of this role is AWS-based data engineering, analytics architecture, and modern data platform design, with SAP knowledge considered a strong advantage. Key job responsibilities * Lead the design, implementation, and support of enterprise data and analytics solutions on AWS. * Architect scalable data platforms using AWS services such as Amazon Redshift, Amazon S3, AWS Glue, Amazon Athena, Amazon QuickSuite, AWS Lambda, and related AWS data services. * Define and implement data ingestion, transformation, storage, semantic modeling, reporting, and analytics patterns across structured and semi-structured data sources. * Design and optimize enterprise data pipelines, batch and near real-time data processing, and reporting architectures. * Ensure data quality, governance, security, and operational controls are built into the platform architecture. * Work closely with business, finance, IT, and application teams to design reliable and scalable data solutions aligned with business requirements. * Develop and maintain architecture standards, design documents, data flow diagrams, and support procedures. * Monitor data pipelines, analytics platforms, and reporting solutions for failures, performance issues, and data quality concerns, and drive corrective actions. * Lead implementation, migration, modernization, and enhancement initiatives across data and analytics platforms. * Support integration with enterprise platforms, including SAP and non-SAP systems where required. Basic Qualifications: - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - 6+ years of data engineering, database engineering, business intelligence or business analytics experience - 8+ years of relevant experience in data engineering, analytics, data warehousing, or enterprise data platform implementation and support. - Experience designing scalable data pipelines and cloud-based analytics solutions across complex enterprise environments. - Excellent analytical, problem-solving, and stakeholder management skills, with the ability to work independently and as part of a team. Preferred Qualifications: - Knowledge of SAP data and analytics platforms such as SAP S/4HANA, BW, Datasphere, or SAC is good to have. - Experience with real-time or event-driven data processing patterns. - Experience with data lake, data warehouse, and hybrid analytics architecture patterns. - Experience with enterprise reporting, KPI frameworks, and dashboard design. - Knowledge of finance, supply chain, or enterprise operational reporting domains. - Experience leading data modernization or cloud transformation initiatives. 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 and Analytics Architect at ADCI HYD. Skills: Data architecture, AWS data services, Data platform design. Lead design of data solutions. Lead implementation of data solutions", "postedDate" : "2026-06-13T14:22:44.066", "createdAt" : "2026-06-13T14:22:44.066", "lastUpdated" : "2026-06-15T07:27:32.772", "ingestTimestamp" : "2026-06-13T14:22:44.066", "mongoId" : "69cf3f062beec4dd3d9340ff", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10382143/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data engineering", "Database engineering", "Business intelligence", "Business analytics", "Data warehousing", "Enterprise data platform", "Data pipelines", "Analytics solutions", "Data processing", "Reporting architectures", "Data quality", "Data governance", "Data security", "Operational controls", "Data integration", "Data architecture", "AWS data services", "Data platform design", "Analytics architecture", "Data ingestion", "Data transformation", "Data storage", "Semantic modeling", "Reporting", "Analytics patterns", "Business requirements", "Architecture standards", "Data flow diagrams", "Support procedures", "Performance issues", "Data quality concerns", "Corrective actions", "Implementation initiatives", "Migration initiatives", "Modernization initiatives", "Enhancement initiatives", "Platform integration", "FinTech", "SAP data", "Finance reporting", "Supply chain reporting", "Enterprise operational reporting" ], "skillCount" : 42, "jobCategory" : "operations", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2c92ed74d8ee00a0986e18", "title" : "Data Engineer with Databricks", "company" : "Xebia", "industry" : "Consulting", "salary" : { "min" : 200000.0, "max" : 300000.0, "currency" : "PLN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Senior Data Engineer with Databricks in Poland, adjusted for the technology industry and company size." }, "location" : "Poland", "locations" : [ "Poland" ], "certifications" : [ "Databricks certification" ], "timestamp" : "2026-06-16T04:22:07.120", "fingerprint" : "cf05077c996b927edb4318cee3e1ff382566b7672fd27250236455dbae7c591b", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/xebiacee/jobs/6011045004", "externalId" : "6011045004", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Poland", "continent" : "eu", "workMode" : "onsite" } ], "locationText" : "Poland", "technicalSkills" : "Python, Databricks, PySpark, AWS, Azure, GCP, Snowflake, Azure Key Vault, Azure Logic Apps, Azure Service Bus, Azure DevOps, Unity Catalog", "professionalSkills" : [ "System design", "Data modeling", "ETL design", "ELT design", "Orchestration", "Deployment automation", "Troubleshooting", "Continuous improvement" ], "hardSkillsList" : [ "Batch processing", "Real-time processing", "Data integration", "Data warehousing", "Data orchestration", "Model deployment", "Secrets management", "Process automation", "Data governance", "Event-driven workflows", "CI/CD", "Testing", "Monitoring" ], "softSkillsList" : [ "Leadership", "Mentoring", "Critical thinking" ], "hardSkills" : [ { "name" : "Batch processing", "level" : "intermediate" }, { "name" : "Real-time processing", "level" : "intermediate" }, { "name" : "Data integration", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "Data orchestration", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" }, { "name" : "Secrets management", "level" : "intermediate" }, { "name" : "Process automation", "level" : "intermediate" }, { "name" : "Data governance", "level" : "intermediate" }, { "name" : "Event-driven workflows", "level" : "intermediate" }, { "name" : "CI/CD", "level" : "intermediate" }, { "name" : "Testing", "level" : "intermediate" }, { "name" : "Monitoring", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" }, { "name" : "Critical thinking" } ], "majorSkills" : "Data Engineering, Databricks, PySpark, Azure", "majorSkillsList" : [ "Data Engineering", "Databricks", "PySpark", "Azure" ], "coreResponsibilities" : "Build data pipelines, Maintain data pipelines, Optimize data pipelines, Integrate data sources, Maintain analytical database, Enhance analytical database, Support analytical database, Collaborate with stakeholders, Deliver data products, Identify technical debt, Improve platform reliability, Improve platform maintainability, Improve platform performance, Build Databricks Workflows, Manage Databricks Workflows, Develop PyFunc models, Deploy PyFunc models, Maintain PyFunc models, Implement secure secrets management, Implement configuration management, Automate data flows, Automate business processes, Design ETL pipelines, Develop ETL pipelines, Optimize ETL pipelines, Design ELT pipelines, Develop ELT pipelines, Optimize ELT pipelines, Govern data assets, Manage data assets, Implement messaging workflows, Implement event-driven workflows, Collaborate with architects, Collaborate with analysts, Collaborate with data scientists, Collaborate with engineering teams, Deliver end-to-end data solutions, Contribute to CI/CD processes, Contribute to deployment automation, Ensure high quality, Take ownership of technical areas, Support architectural decisions, Mentor team members", "teamCollaboration" : "Cross-functional teams; Architects; Analysts; Data scientists; Engineering teams; Business stakeholders", "projectManagementSkills" : [ "Agile delivery", "Engineering best practices" ], "domainKnowledge" : "Data engineering best practices; Modern data platform architectures; Medallion Architecture; Data Lakehouse principles; Event-driven architectures; Distributed data processing; GenAI; AI-augmented development", "domainList" : [ "data-engineering-best-practices", "modern-data-platform-architectures", "medallion-architecture", "data-lakehouse-principles", "event-driven-architectures", "distributed-data-processing", "genai", "ai-augmented-development" ], "domainSpecificKnowledge" : [ "Data engineering best practices", "Modern data platform architectures", "Medallion Architecture", "Data Lakehouse principles", "Event-driven architectures", "Distributed data processing", "GenAI", "AI-augmented development" ], "toolProficiency" : [ "Databricks", "Azure DevOps", "Azure Key Vault", "Azure Logic Apps", "Azure Service Bus", "Unity Catalog", "GitHub Copilot", "Claude Code", "Cursor" ], "communicationSkills" : "Technical communication; Business communication", "continuousLearning" : "Continuous professional development; Knowledge sharing", "innovationCreativity" : "Explore new technologies; Experiment with AI", "problemSolvingSkills" : "Problem-solving; Identify issues; Identify opportunities; Identify improvement areas", "specialRequirements" : "Work permit required", "qualificationsBasic" : "3+ years commercial experience, Senior engineering experience, Hands-on Python knowledge, Databricks experience, PySpark experience, Modern data analytics platforms experience, Azure cloud environments experience, Modular system components design, Data engineering best practices understanding, Medallion Architecture familiarity, Business requirements translation, Problem-solving skills, Organizational skills, Azure DevOps experience, CI/CD practices experience, Agile delivery environments experience, Work from EU region, Work permit required", "qualificationsPreferred" : "Databricks certification, Infrastructure as Code experience, MLOps practices experience, Kubernetes experience, Requirements engineering experience, Business analysis awareness, Event-driven architectures familiarity, Distributed data processing systems familiarity, GenAI structured application experience, Emerging AI-driven practices interest", "remoteFriendly" : true, "rawDescription" : "Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. You will be: build, maintain, and optimize data pipelines using Python, Databricks, and PySpark for batch and real-time processing, integrate data from multiple internal and external sources into the organization’s analytical platform, maintain, enhance, and support the analytical database and the surrounding data ecosystem, collaborate with business stakeholders and cross-functional teams to deliver data products that meet business needs and timelines, identify technical debt and continuously improve platform reliability, maintainability, and performance, build and manage Databricks Workflows for large-scale data orchestration, develop, deploy, and maintain PyFunc models within production environments, implement secure secrets and configuration management using Azure Key Vault, automate data flows and business processes using Azure Logic Apps, design, develop, and optimize ETL and ELT pipelines following data engineering best practices, govern and manage data assets using Unity Catalog and Data Lakehouse principles, implement messaging and event-driven workflows using Azure Service Bus, collaborate closely with architects, analysts, data scientists, and engineering teams to deliver end-to-end data solutions, contribute to CI/CD processes and deployment automation using Azure DevOps, ensure high quality through testing, monitoring, troubleshooting, and continuous improvement activities, depending on seniority, take ownership of technical areas, support architectural decisions, and mentor less experienced team members, Your profile: minimum 3 years of commercial experience in software engineering, data engineering, or related fields, experience working in senior engineering, technical leadership, or highly autonomous delivery roles, strong hands-on knowledge of Python as the primary development language, strong experience with Databricks and PySpark in production environments, proven experience building and supporting modern data analytics platforms, practical experience working within Azure cloud environments or similar cloud ecosystems, experience designing modular, reusable, scalable, and maintainable system components, strong understanding of data engineering best practices and modern data platform architectures, familiarity with Medallion Architecture or equivalent data modeling and design patterns, ability to gather, clarify, and translate business requirements into technical solutions, strong problem-solving, communication, and organizational skills, proactive approach to identifying issues, opportunities, and improvement areas, experience working with Azure DevOps and CI/CD practices, excellent communication skills and ability to collaborate with technical and business stakeholders, experience working within Agile delivery environments and engineering best practices, quick learner with a strong interest in new technologies and continuous professional development, Practical experience using AI-powered assistants (e. g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. Work from the European Union region and a work permit are required. Nice to have: Databricks certification, experience with Infrastructure as Code technologies such as Terraform or ARM templates, experience with MLOps practices and automation of machine learning and data pipelines, experience working with Kubernetes or other container orchestration platforms, requirements engineering experience and business analysis awareness, familiarity with event-driven architectures and distributed data processing systems, Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work. Interest in and familiarity with emerging AI-driven practices (e. g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches. Recruitment Process: CV review – HR call – Interview – Client Interview – Decision", "summaryDescription" : "Data Engineer with Databricks at Xebia. Skills: Data Engineering, Databricks, PySpark, Azure. Build data pipelines. Maintain data pipelines", "postedDate" : "2026-06-14T19:12:25.152", "createdAt" : "2026-06-14T19:12:25.152", "lastUpdated" : "2026-06-16T04:22:07.120", "ingestTimestamp" : "2026-06-14T19:12:25.152", "mongoId" : "6a2c92ed74d8ee00a0986e18", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Batch processing", "Real-time processing", "Data integration", "Data warehousing", "Data orchestration", "Model deployment", "Secrets management", "Process automation", "Data governance", "Event-driven workflows", "CI/CD", "Testing", "Monitoring", "Leadership", "Mentoring", "Critical thinking", "Data Engineering", "Databricks", "PySpark", "Azure", "System design", "Data modeling", "ETL design", "ELT design", "Orchestration", "Deployment automation", "Troubleshooting", "Continuous improvement", "Agile delivery", "Engineering best practices", "Data engineering best practices", "Modern data platform architectures", "Medallion Architecture", "Data Lakehouse principles", "Event-driven architectures", "Distributed data processing", "GenAI", "AI-augmented development", "Databricks certification", "Azure DevOps", "Azure Key Vault", "Azure Logic Apps", "Azure Service Bus", "Unity Catalog", "GitHub Copilot", "Claude Code", "Cursor" ], "skillCount" : 47, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a30511af292fd229cefa673", "title" : "Solutions Architect IV- Data and Analytics", "industry" : "IT", "salary" : { "min" : 85000.0, "max" : 135000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Solutions Architect IV in Bulgaria, adjusted for the technology industry and remote work." }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T11:33:50.217", "fingerprint" : "1a58dd7bf18f2efdc2c046d8f3f4e1b90f08c87a7ddd6966c933a1be53219368", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/2b7d6fbe-231c-4004-828c-8606bceba0b0/apply", "externalId" : "2b7d6fbe-231c-4004-828c-8606bceba0b0", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Oracle Analytics Cloud, ETL, Power BI", "professionalSkills" : [ "Data modeling", "Data governance", "Self-service BI", "User access management", "Data quality processes", "ETL optimization", "System troubleshooting", "Project planning", "Stakeholder management" ], "hardSkillsList" : [ "Data ingestion", "Data transformation", "Reporting logic", "Data cleansing", "Reporting needs" ], "softSkillsList" : [ "Problem-solving" ], "hardSkills" : [ { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Reporting logic", "level" : "intermediate" }, { "name" : "Data cleansing", "level" : "intermediate" }, { "name" : "Reporting needs", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Problem-solving" } ], "majorSkills" : "Data architecture, Data analytics, Business intelligence", "majorSkillsList" : [ "Data architecture", "Data analytics", "Business intelligence" ], "coreResponsibilities" : "Develop and maintain stakeholder relationships, Ensure data and analytics solutions align with business, Enhance and maintain stability of OAC environments, Enhance and maintain performance of OAC environments, Enhance and maintain scalability of OAC environments, Design data ingestion strategies, Support data ingestion strategies, Establish data governance standards, Maintain data governance standards, Document data sources, Document transformations, Document reporting logic, Promote self-service BI adoption, Promote visualization best practices, Manage user access, Manage security, Manage provisioning for analytics platforms, Support data quality processes, Validate data, Cleanse data, Optimize ETL, Collaborate with business users, Collaborate with IT teams, Troubleshoot system issues, Deliver enhancements, Support reporting needs, Participate in SDLC processes, Participate in project planning, Participate in Agile ceremonies, Communicate status updates, Communicate risks, Contribute to dashboard development, Contribute to report creation, Contribute to migration efforts, Lift and shift OAC content into Power BI", "teamCollaboration" : "Cross-functional collaboration efforts; Business users; IT teams", "projectManagementSkills" : [ "Agile ceremonies", "Project planning", "SDLC processes" ], "domainKnowledge" : "Data lake architectures; Modern data warehouse architectures; Enterprise BI architectures", "domainList" : [ "data-lake-architectures", "modern-data-warehouse-architectures", "enterprise-bi-architectures" ], "domainSpecificKnowledge" : [ "Data lake architectures", "Modern data warehouse architectures", "Enterprise BI architectures" ], "toolProficiency" : [ "Oracle Analytics Cloud", "Power BI" ], "communicationSkills" : "Presentation; Stakeholder management; Explain analytical insights", "documentationSkills" : "Documentation of data sources; Documentation of transformations; Documentation of reporting logic", "problemSolvingSkills" : "Problem-solving abilities", "specialRequirements" : "Willingness to travel periodically", "qualificationsBasic" : "Bachelor's degree in Computer Science, Information Systems, Business Administration, or related field, 5+ years of experience in BI, data analytics, or data architecture roles, Experience with relational databases, Data modeling concepts, ETL processes, Flat file data integration, Deep understanding of data analytics platforms, Reporting frameworks, Enterprise BI architectures, Ability to translate business requirements into technical data solutions, Explain analytical insights in simple terms, Experience working with stakeholders to define priorities, Gather requirements, Deliver data-driven solutions, Knowledge of Agile/Scrum methodologies, Basic project management principles, Communication skills, Presentation skills, Stakeholder management skills", "qualificationsPreferred" : "Hands-on experience with Microsoft Power BI or similar data visualization tools, Familiarity with data lake concepts, Emerging modern data warehouse architectures", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Develop and maintain strong stakeholder relationships to ensure data and analytics solutions align with evolving business requirements and priorities. Enhance and maintain stability, performance, and scalability of existing Oracle Analytics Cloud (OAC) environments. Design and support data ingestion strategies for modern data lake architectures using ETL tools, flat file processing, and integration frameworks. Establish and maintain data governance standards, including documentation of data sources, transformations, and reporting logic. Promote self-service BI adoption and visualization best practices across the organization using OAC and Power BI platforms. Manage user access, security, and provisioning for analytics platforms, ensuring appropriate governance and compliance. Support data quality processes including validation, cleansing, and ETL optimization to ensure reliable reporting outputs. Collaborate with business users and IT teams to troubleshoot system issues, deliver enhancements, and support reporting needs. Participate in SDLC processes, project planning, and Agile ceremonies while ensuring timely communication of status updates and risks. Contribute to dashboard development, report creation, and migration efforts including the “lift and shift” of legacy OAC content into Power BI. Requirements: Bachelor’s degree in Computer Science, Information Systems, Business Administration, or related field. 5+ years of experience in BI, data analytics, or data architecture roles covering design, development, implementation, and support of enterprise analytics solutions. Strong experience with relational databases, data modeling concepts, ETL processes, and flat file data integration. Hands-on experience with Microsoft Power BI or similar data visualization tools strongly preferred. Deep understanding of data analytics platforms, reporting frameworks, and enterprise BI architectures. Strong ability to translate business requirements into technical data solutions and explain analytical insights in simple terms. Experience working with stakeholders to define priorities, gather requirements, and deliver data-driven solutions. Familiarity with data lake concepts and emerging modern data warehouse architectures. Knowledge of Agile/Scrum methodologies and basic project management principles. Strong communication, presentation, and stakeholder management skills across technical and non-technical audiences. Self-starter mindset with strong problem-solving abilities and ability to lead cross-functional collaboration efforts. Willingness to travel periodically as required. Benefits: Competitive base salary with performance-based incentive compensation. Comprehensive health coverage including medical, dental, and vision insurance. Life insurance, disability coverage, and additional voluntary benefit options. Immediate eligibility for 401(k) with employer matching contributions. Generous paid time off including 80 hours (10 days) of company holidays annually. Adoption benefits and family support programs. Inclusive work environment with equal opportunity employment practices. Exposure to modern data architecture transformation and enterprise BI modernization initiatives. ## 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" : "Solutions Architect IV- Data and Analytics. Skills: Data architecture, Data analytics, Business intelligence. Develop and maintain stakeholder relationships. Ensure data and analytics solutions align with business", "postedDate" : "2026-06-15T10:16:20.862", "createdAt" : "2026-06-15T10:16:20.862", "lastUpdated" : "2026-06-16T11:33:50.217", "ingestTimestamp" : "2026-06-16T03:20:53.708", "mongoId" : "6a30511af292fd229cefa673", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Data ingestion", "Data transformation", "Reporting logic", "Data cleansing", "Reporting needs", "Problem-solving", "Data architecture", "Data analytics", "Business intelligence", "Data modeling", "Data governance", "Self-service BI", "User access management", "Data quality processes", "ETL optimization", "System troubleshooting", "Project planning", "Stakeholder management", "Agile ceremonies", "SDLC processes", "Data lake architectures", "Modern data warehouse architectures", "Enterprise BI architectures", "Oracle Analytics Cloud", "Power BI" ], "skillCount" : 25, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "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. 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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" : "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" : "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" : "68b706997fc9a711f0f6fe81", "title" : "Senior Data Scientist - Data and Machine Learning, WWPS ProServe Data and Machine Learning", "company" : "Amazon Web Services, Inc.", "industry" : "Data Science, Science, Cloud Computing", "salary" : { "min" : 143300.0, "max" : 247600.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Herndon, Virginia, USA", "locations" : [ "Herndon, Virginia, USA" ], "timestamp" : "2026-06-15T06:03:22.811", "fingerprint" : "2de507a2af9713958cf19fc7bc76811d52243f83d9bf8296e6df9008d561a0ec", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3051327/apply", "externalId" : "17bd976f-c327-4f8f-82fd-e01156aa798f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Herndon", "state" : "Virginia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "38.9695316,-77.3859479" } ], "locationText" : "Herndon, Virginia, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI algorithms, Generative AI, Machine Learning, Large Language Models, Python, Tensorflow, Keras, PyTorch, MXNet, AWS, SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, JAX", "professionalSkills" : [ "Business acumen", "Data science", "AI methods" ], "hardSkillsList" : [ "Data mining", "Numerical optimization", "Deep learning", "Machine learning" ], "hardSkills" : [ { "name" : "Data mining", "level" : "intermediate" }, { "name" : "Numerical optimization", "level" : "intermediate" }, { "name" : "Deep learning", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Machine Learning, Data Science", "majorSkillsList" : [ "Generative AI", "Machine Learning", "Data Science" ], "coreResponsibilities" : "Research AI algorithms, Design AI algorithms, Develop AI algorithms, Evaluate AI algorithms, Interact with customers, Understand business problem, Aid customers in implementation of AI solutions, Deliver briefing sessions to customers, Deliver deep dive sessions to customers, Guide customer on adoption patterns, Guide customer on paths to production, Create best practice recommendations, Deliver best practice recommendations, Create tutorials, Deliver tutorials, Create blog posts, Deliver blog posts, Create sample code, Deliver sample code, Create presentations, Deliver presentations, Provide customer feedback, Provide market feedback", "teamCollaboration" : "AI/ML scientists; Architects; Product teams; Engineering teams", "domainKnowledge" : "Generative AI; Large Language Models; US Intelligence Community", "domainList" : [ "generative-ai", "large-language-models", "us-intelligence-community" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models", "US Intelligence Community" ], "toolProficiency" : [ "Tensorflow", "Keras", "PyTorch", "MXNet", "JAX" ], "communicationSkills" : "Customer briefings; Deep dive sessions; Executive stakeholder presentations", "documentationSkills" : "Best practice recommendations; Tutorials; Blog posts; Sample code; Presentations", "innovationCreativity" : "Drive feature innovation", "problemSolvingSkills" : "Solve complex problems", "specialRequirements" : "TS/SCI with Polygraph, Up to 25% local travel", "qualificationsBasic" : "Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience, 5+ years of experience building models for business applications, Experience with algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning, Experience using Python, Hands on experience building models with deep learning frameworks (i. e. Tensorflow, Keras, PyTorch, MXNet), Current, active US Government Security Clearance of TS/SCI with Polygraph", "qualificationsPreferred" : "Masters or PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, AWS experience preferred, Practical experience in solving complex problems in an applied environment, Hands on experience building models with deep learning frameworks like PyTorch, Tensorflow, or JAX, Experience building applications leveraging GenAI", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you excited to help the US Intelligence Community design, build, and implement AI algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI methods. We build models for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs), text-to-image generation, and other advanced AI capabilities to fit the mission. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced data scientists with a background in both traditional and generative AI who can help our customers understand the opportunities their data presents, and build solutions that earn the customer trust needed for deployment to production systems. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As an Data Scientist, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction - This position may require up to 25% local travel. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences and inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Basic Qualifications: - Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience - 5+ years of experience building models for business applications - Experience with algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning - Experience using Python and hands on experience building models with deep learning frameworks (i.e. Tensorflow, Keras, PyTorch, MXNet) - Current, active US Government Security Clearance of TS/SCI with Polygraph Preferred Qualifications: - Masters or PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field - AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch) - Practical experience in solving complex problems in an applied environment - Hands on experience building models with deep learning frameworks like PyTorch, Tensorflow, or JAX - Experience building applications leveraging GenAI 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. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location 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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Senior Data Scientist - Data and Machine Learning, WWPS ProServe Data and Machine Learning at Amazon Web Services, Inc.. Skills: Generative AI, Machine Learning, Data Science. Research AI algorithms. Design AI algorithms", "postedDate" : "2026-06-13T12:13:39.251", "createdAt" : "2026-06-13T12:13:39.251", "lastUpdated" : "2026-06-15T06:03:22.811", "ingestTimestamp" : "2026-06-13T12:13:39.251", "mongoId" : "68b706997fc9a711f0f6fe81", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3051327/apply", "salaryAnnualMin" : 143300, "salaryAnnualMax" : 247600, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data mining", "Numerical optimization", "Deep learning", "Machine learning", "Generative AI", "Machine Learning", "Data Science", "Business acumen", "Data science", "AI methods", "Large Language Models", "US Intelligence Community", "Tensorflow", "Keras", "PyTorch", "MXNet", "JAX" ], "skillCount" : 17, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a306002f292fd229cf84369", "title" : "Sr. Manager, Statistical Programming and Data Operations", "company" : "Kyowa Kirin North America", "industry" : "Pharma", "salary" : { "min" : 145000.0, "max" : 160000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Princeton, New Jersey, United States", "locations" : [ "Princeton", "New Jersey", "United States" ], "timestamp" : "2026-06-16T08:50:44.103", "fingerprint" : "49d9cfec2d36afaf4e7072ec9fd00eb8eee6a4c344e64335be311f83397963b8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/kyowakirinusa90/jobs/7773426003", "externalId" : "7773426003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Princeton", "state" : "New Jersey", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "40.3496953,-74.6597376" }, { "city" : "San Diego", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "32.7174202,-117.1627720" }, { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "Princeton, New Jersey, United States; San Diego, California, United States; San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "SAS, R, Microsoft Office", "professionalSkills" : [ "Vendor oversight", "Project management", "Data standards" ], "hardSkillsList" : [ "Statistical programming", "CDISC compliant submission", "Regulatory documents" ], "hardSkills" : [ { "name" : "Statistical programming", "level" : "intermediate" }, { "name" : "CDISC compliant submission", "level" : "intermediate" }, { "name" : "Regulatory documents", "level" : "intermediate" } ], "majorSkills" : "Statistical programming, CDISC standards, Vendor management", "majorSkillsList" : [ "Statistical programming", "CDISC standards", "Vendor management" ], "coreResponsibilities" : "Develop TLF shells, Develop CDISC deliverables, Develop TLFs, Participate in vendor selection, Oversee vendor processes, Review Requests for Proposal, Track stat/programming activities, Manage project budget, Manage timeline of deliverables, Ensure statistical deliverables meet timelines, Oversee statistical programming tasks, Manage stat/programming TMFs, Act as subject matter expert, Interface with in-house staff, Participate on project team, Manage cost of activities, Manage timeline of activities, Review protocols, Review case report forms, Review statistical analysis plans, Review specifications for raw data, Review clinical study reports, Review study-related documents, Provide statistical programming input, Prepare CDISC data submission package, Prepare SAS programming for regulatory documents, Provide statistical programming for publications, Provide statistical programming for presentations, Provide ad-hoc analyses, Provide post-hoc analyses, Conduct programming QC reviews, Support departmental initiatives, Improve programming activities, Coordinate with Japanese colleagues, Liaise regarding global procedures, Liaise regarding global processes, Liaise regarding global standards", "teamCollaboration" : "Cross-regional staffs; Project team; Japanese colleagues", "projectManagementSkills" : [ "Timeline management", "Budget management" ], "domainKnowledge" : "Clinical trials; Drug development; ICH guidelines; Regulatory guidance; Life sciences industry; Biostatistics; CDISC standards", "domainList" : [ "clinical-trials", "drug-development", "ich-guidelines", "regulatory-guidance", "life-sciences-industry", "biostatistics", "cdisc-standards" ], "domainSpecificKnowledge" : [ "Clinical trials", "Drug development", "ICH guidelines", "Regulatory guidance", "Life sciences industry", "Biostatistics", "CDISC standards" ], "toolProficiency" : [ "SAS", "Microsoft Office" ], "documentationSkills" : "TLF shells; CDISC datasets; Regulatory documents", "specialRequirements" : "FDA inspections", "qualificationsBasic" : "Bachelor's Degree or higher in Computer Science, Statistics, or related discipline, Six or more years of experience with a Master's degree, Eight or more years of experience with a Bachelor's degree, Proven experience in statistical programming for clinical trials, Experience in study oversight of statistical analysis for clinical trials, Demonstrated expertise in CDISC standards, Excellent proficiency in SAS", "qualificationsPreferred" : "Experience in data integration for ISS/ISE, Experience using SAS-LSAF, Advance skill in R", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Kyowa Kirin is a fast-growing global specialty pharmaceutical company that applies state-of-the-art biotechnologies to discover and deliver novel medicines in four disease areas: bone and mineral; intractable hematologic; hematology oncology; and rare disease. A Japan-based company, our goal is to translate science into smiles by delivering therapies where no adequate treatments currently exist, working from drug discovery to product development and commercialization. In North America, we are headquartered in Princeton, NJ, with offices in California, North Carolina, and Mississauga, Ontario. Summary: Manager, Statistical Programming and Data Operations (SPDO) in Biostatistics is responsible for vendor oversight and management to deliver the high-quality tables, listings, and figures (TLFs), as well as CDISC datasets for clinical trials and integrated statistical analysis intended for regulatory submissions, interfacing with cross-regional staffs in establishing and maintaining global data standards and department procedures. Essential Functions: Vendor Oversight and Management • Responsible for developing TLF shells, CDISC deliverables, and TLFs in collaboration with stat/programming vendors. • Participate in vendor selection/oversight processes: Create and/or review Requests for Proposal (RFP); track the progress of stat/programming activities and the project budget for stat/programming vendor; and manage the timeline of stat/programming deliverables. • Collaborate with stat/programming vendors to ensure all statistical deliverables from the vendor meet timelines with quality. Oversee all aspects of statistical programming tasks performed by the vendor. • Manage the stat/programming related TMFs in collaboration with stat/programming vendors and act as a subject matter expert at FDA inspections. Internal Collaboration • Interface with in-house staff: Participate on project team meetings; and manage the cost and timeline of stat/programming activities in collaboration with each project manager. • Review protocols, case report forms, statistical analysis plans, specifications for raw data, clinical study reports, and the other study-related documents. • Collaborate with biostatistician to provide statistical programming input on project topics and issues. Statistical Programming • Responsible for preparation of CDISC data submission package and SAS programming for regulatory documents (e. g. Response to information requests from HA; Integrated summaries; BIMO; and DSUR). • Provide statistical programming for publications and presentations, ad-hoc and post-hoc analyses of clinical study data. • Conduct programming QC reviews of vendor deliverables in accordance with internal guidelines and work instructions. • Support departmental initiatives related to process building/improvement of programming activities. • Coordinate and liaise with our Japanese colleagues, as needed, regarding global procedures, processes, and standards. Requirements: Education Bachelor’s Degree or higher in Computer Science, Statistics, or closely related discipline. Experience • Proven experience in statistical programming for clinical trials in the life sciences industry: six or more years with a Master’s degree, or eight or more years with a Bachelor’s degree. • Experience in study oversight of statistical analysis for clinical trials in the life science industry • Demonstrated expertise in CDISC standards and CDISC compliant submission requirements. • Experience in data integration for ISS/ISE across multiple studies for regulatory submissions (preferred) • Experience in using SAS-LSAF (i. e. Life Science Analytics Framework), including its repository and programming environment (preferred) Technical Skills • Excellent proficiency in SAS (required); Advance skill in R (preferred). • Highly skilled in Microsoft Office applications (Word, PowerPoint, Excel, Outlook). • Familiarity with ICH guidelines (especially E9) and other regulatory guidance. • Solid understanding of development, regulatory and commercial aspects of drug development. The anticipated salary for this position will be $145,000 to $160,000. The actual salary offered for this role at commencement of employment may vary based on several factors including but not limited to relevant experience, skill set, qualifications, education (including applicable licenses and certifications, job-based knowledge, location, and other business and organizational needs. The listed salary is just one component of the overall compensation package. At Kyowa Kirin North America we provide a comprehensive range of benefits including: 401K with company match Annual Bonus Program (Sales Bonus for Sales Jobs) Generous PTO and Holiday Schedule which includes Summer and Winter Shut-Downs, Sick Days and, Volunteer Days Healthcare Benefits (Medical, Dental, Prescription Drugs and Vision) HSA Kyowa Kirin is not responsible for any fees related to unsolicited resumes. #Hybrid #Princeton", "summaryDescription" : "Sr. Manager, Statistical Programming and Data Operations at Kyowa Kirin North America. Skills: Statistical programming, CDISC standards, Vendor management. Develop TLF shells. Develop CDISC deliverables", "postedDate" : "2026-06-15T23:25:02.678", "createdAt" : "2026-06-15T23:25:02.678", "lastUpdated" : "2026-06-16T08:50:44.103", "ingestTimestamp" : "2026-06-15T23:25:02.678", "mongoId" : "6a306002f292fd229cf84369", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 145000, "salaryAnnualMax" : 160000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Statistical programming", "CDISC compliant submission", "Regulatory documents", "CDISC standards", "Vendor management", "Vendor oversight", "Project management", "Data standards", "Timeline management", "Budget management", "Clinical trials", "Drug development", "ICH guidelines", "Regulatory guidance", "Life sciences industry", "Biostatistics", "SAS", "Microsoft Office" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Manager", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Pharma", "llmIndustryConfidence" : 0.95 }, { "id" : "69cf19022beec4dd3d8f336b", "title" : "Project Lead - Data and Analytics", "company" : "Collectiv", "industry" : "Consulting", "salary" : { "min" : 135000.0, "max" : 185000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Lead Project Lead - Data and Analytics in Chicago, adjusted for the consulting industry and company size." }, "location" : "Chicago, IL", "locations" : [ "Chicago", "IL" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-15T09:19:11.588", "fingerprint" : "f12367e374a02b40109d314dabfb83ad4c792739946c6417dea0b89ea7985c3a", "source" : "breezyhr", "language" : "en", "applyUrl" : "https://collectiv.breezy.hr/p/dd8333538616-project-lead-data-and-analytics", "externalId" : "dd8333538616", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Chicago", "state" : "Illinois", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "41.8755616,-87.6244212" } ], "locationText" : "Chicago, Illinois, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "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, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Project leadership", "Business analysis", "Stakeholder management" ], "hardSkillsList" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Data science", "level" : "intermediate" }, { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "ML/AI", "level" : "intermediate" }, { "name" : "Business intelligence", "level" : "intermediate" }, { "name" : "Analytics engineering", "level" : "intermediate" }, { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data science, Data engineering, ML/AI, Business intelligence", "majorSkillsList" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence" ], "coreResponsibilities" : "Lead client-facing initiatives, Manage initiatives from discovery, Deliver client-facing initiatives", "projectManagementSkills" : [ "Project leadership" ], "domainKnowledge" : "Cloud data services; ML frameworks; BI platforms; Cloud data stacks", "domainList" : [ "cloud-data-services", "ml-frameworks", "bi-platforms", "cloud-data-stacks" ], "domainSpecificKnowledge" : [ "Cloud data services", "ML frameworks", "BI platforms", "Cloud data stacks" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "qualificationsBasic" : "5+ years experience, SQL proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "Job Title: Project Lead - Data and Analytics We are seeking a results-driven Project Lead Consultant to lead client-facing Data and AI initiatives from discovery through delivery. This role is ideal for a professional who combines strong project leadership, business analysis, and stakeholder manag", "summaryDescription" : "Project Lead - Data and Analytics at Collectiv. Skills: Data science, Data engineering, ML/AI, Business intelligence. Lead client-facing initiatives. Manage initiatives from discovery", "createdAt" : "2026-06-14T03:13:45.271", "lastUpdated" : "2026-06-15T09:19:11.588", "ingestTimestamp" : "2026-06-14T03:13:45.271", "mongoId" : "69cf19022beec4dd3d8f336b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 135000, "salaryAnnualMax" : 185000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Leadership", "Project leadership", "Business analysis", "Stakeholder management", "Cloud data services", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 33, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Consulting", "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" : "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" : "6a3055f1f292fd229cf23389", "title" : "Support and Data Operations Associate (Fixed-term)", "company" : "Foursquare", "industry" : "Finance", "salary" : { "min" : 1000000.0, "max" : 1500000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Support and Data Operations Associate in Belgrade, Serbia, adjusted for the technology industry and company size." }, "location" : "Serbia", "locations" : [ "Serbia" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T08:56:17.647", "fingerprint" : "aaf5559b6dd261874f5f77a1afd61a6fd75d245824898322671fec42e45798b8", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/foursquare/b98303fd-481a-4f08-9feb-451f7c9b179e/application", "externalId" : "b98303fd-481a-4f08-9feb-451f7c9b179e", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Belgrade", "country" : "Serbia", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "44.8153318,20.4456588" } ], "locationText" : "Belgrade, Serbia", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Tableau, Power BI, Looker, Metabase, Superset, Qlik, MicroStrategy, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure, S3, Glue, SageMaker, Athena, Vertex AI, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "Machine learning", "Business intelligence", "Data analytics", "Quantitative analysis", "Data modelling" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "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" ], "toolProficiency" : [ "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure", "S3", "Glue", "SageMaker", "Athena", "Vertex AI", "Synapse", "ML Studio" ], "qualificationsBasic" : "SQL proficiency, 5+ years of experience", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow, Experience with Snowflake, Experience with BigQuery, Experience with Redshift, Experience with Databricks, Experience with dbt, Experience with Fivetran, Experience with Airflow, Experience with dbt Cloud, Experience with Delta Lake, Experience with AWS SageMaker, Experience with GCP Vertex AI, Experience with Azure ML Studio", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Foursquare Foursquare is the leading independent location technology and data cloud platform, helping businesses connect the digital and physical worlds with precision and purpose. Our products power everything from market analytics to targeted experiences, relied on by some of the world’s most iconic brands. But what makes Foursquare truly special is how we work. We're a team of builders, problem-solvers, and collaborators who care deeply about impact – both in the products we ship and the way we show up for each other. Great outcomes come from strong collaboration and shared ownership, and we believe growth happens through real challenges – whether that’s leveling up a skill, tackling unfamiliar problems, or pushing a project forward in a new way. If you're excited by cutting-edge tech and a culture that values both autonomy and teamwork, you’ll thrive here. About the Position Foursquare is looking for a Support and Data Operations Associate to join our team in our Belgrade office; on a hybrid schedule of Tuesday, Wednesday, Thursday in office. We are looking for an inquisitive, adaptable, and highly motivated Data Support Associate to join our team. In this role, you will be primarily focused on executing web crawls, manipulating data, and utilizing internal pipeline tools to ensure data quality and availability. This is an internally focused, highly technical role where persistence, vigilance, and the ability to learn and iterate quickly are essential. If you enjoy solving technical puzzles, building and maintaining data flows, and continuously learning new skills, we want you on our team! Please note that this is a fixed-term position for an initial period of one year, with the possibility of extension. In this role, you’ll - Web Crawling & Extraction: Execute and manage web crawling initiatives, extracting data, and adapting quickly when target site structures change. - Data Manipulation & Pipelines: Utilize internal tools to perform data cleanup, matching, and transformations to ensure high data quality and reliability. - Technical Troubleshooting: Be vigilant in monitoring data pipelines; investigate issues, read and interpret log files, implement workarounds, and escalate complex technical problems. - Continuous Improvement: Learn and adapt to new internal tools and technical processes rapidly, iterating on existing workflows to improve efficiency. - Documentation: Create and maintain technical process documentation and how-to guides to empower internal teams What you’ll need - Proficient level of written and verbal English - 1+ years of experience working in data-oriented customer operations, technical support, analytics, or similar roles. - Proficiency in Python or Scala, with strong SQL skills. - Proficiency in Regular Expressions (Regex) for pattern matching, data extraction, validation, and web content processing. - Familiarity with data analysis tools and libraries (e.g., PySpark, pandas), web crawling concepts and execution. - General technical troubleshooting skills: ability to read/interpret/transform log files, comfort navigating command-line interfaces (CLI) and APIs, and a strong capacity for independent research. - Your own unique talents! If you don’t meet 100% of the qualifications outlined above, we encourage and welcome you to still apply! Benefits and Perks - 25 days of paid vacation – take the time you need to rest and recharge - Private medical insurance – comprehensive coverage for you and your family - FitPass – flexible access to gyms, wellness classes, and sports facilities across Serbia - Hybrid work schedule – in-person collaboration Tuesday–Thursday, with company-paid lunch on office days - Growth Investment Program – funding and resources to support your personal and professional development - Tech setup – we’ll provide a company laptop and the essentials to help you get up and running smoothly Things to Know Foursquare is proud to foster an inclusive environment, free from discrimination. We believe that building the best products starts with bringing together diverse perspectives and backgrounds — it’s how we create better experiences for both our users and our team. We value every voice, and we encourage you to be part of building a company and products we love. Foursquare is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Foursquare Privacy Policy https://location.foursquare.com/legal/privacy-center/applicant/", "summaryDescription" : "Support and Data Operations Associate (Fixed-term) at Foursquare. 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Implement retrieval systems, Develop ontologies, Develop entity mappings, Develop knowledge graphs, Maintain semantic contracts, Maintain metadata systems, Maintain lineage tracking, Support ML lifecycle workflows, Support LLM lifecycle workflows, Build APIs for agents, Build context stores for agents, Build tool interfaces for agents, Implement data governance frameworks, Implement RBAC, Implement PII handling, Implement schema validation, Implement data quality monitoring, Implement compliance-ready audit logging", "teamCollaboration" : "Global engineering teams; Enterprise-scale AI transformation projects", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "Cloud-native tools; Distributed systems; AI infrastructure; Production AI/ML data infrastructure; Production LLM data infrastructure; RAG environments; MLOps practices; Data governance frameworks; Cloud ecosystems; Containerized environments; AI/LLM tooling; Autonomous agents", "domainList" : [ "cloud-native-tools", 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systems", "qualificationsBasic" : "7+ years of experience in data engineering, 2+ years of experience building production AI/ML or LLM-related data infrastructure, Expertise in Python, SQL, PySpark, Snowflake, Delta Lake, Kafka, and Spark Structured Streaming, Hands-on experience with vector databases, embedding pipelines, and retrieval systems in production RAG environments, Solid understanding of MLOps practices, Knowledge of data governance, security, compliance, and data quality frameworks, Experience working with cloud ecosystems such as AWS or Azure, Experience with containerized environments (Docker, Kubernetes)", "qualificationsPreferred" : "Familiarity with AI/LLM tooling such as LangChain, LlamaIndex, OpenAI/Claudeedrock APIs, and FastAPI", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "## Accountabilities Data Pipeline Engineering: Build, optimize, and maintain robust batch and streaming data pipelines using modern cloud-native tools such as Snowflake, PySpark, Delta Lake, and Kafka, ensuring reliability, scalability, and performance. RAG & Retrieval Infrastructure: Design and implement end-to-end retrieval systems including embedding pipelines, vector databases, hybrid search, chunking strategies, and ranking mechanisms to optimize AI context relevance. Semantic & Knowledge Layer Development: Develop ontologies, entity mappings, and knowledge graphs while maintaining semantic contracts, metadata systems, and lineage tracking for AI and ML use cases. ML/LLMOps Enablement: Support ML and LLM lifecycle workflows including dataset curation, feature engineering, model evaluation, experiment tracking, and production monitoring. Agentic Data Systems: Build APIs, context stores, and tool interfaces that enable autonomous agents, including observability for reasoning traces, tool calls, and contextual outputs. Governance & Data Quality: Implement robust data governance frameworks including RBAC, PII handling, schema validation, data quality monitoring, and compliance-ready audit logging systems. Requirements This role requires a highly experienced data engineering professional with strong cloud, distributed systems, and AI infrastructure expertise. The ideal candidate combines deep technical execution with architectural thinking and hands-on experience building production-grade AI-enabled data systems. 7+ years of experience in data engineering with strong exposure to cloud-based data platforms. 2+ years of experience building production AI/ML or LLM-related data infrastructure at scale. Strong expertise in Python, SQL, PySpark, Snowflake, Delta Lake, Kafka, and Spark Structured Streaming. Hands-on experience with vector databases, embedding pipelines, and retrieval systems in production RAG environments. Solid understanding of MLOps practices including MLflow, CI/CD for ML systems, and automated evaluation frameworks. Strong knowledge of data governance, security, compliance, and data quality frameworks. Experience working with cloud ecosystems such as AWS or Azure and containerized environments (Docker, Kubernetes). Familiarity with AI/LLM tooling such as LangChain, LlamaIndex, OpenAI/Claude/Bedrock APIs, and FastAPI is a plus. Strong problem-solving mindset with the ability to design scalable systems and operate in fast-moving AI environments. Benefits Competitive compensation package aligned with experience and market standards Remote-friendly or hybrid work flexibility depending on team structure Opportunity to work on cutting-edge AI, LLM, and agentic systems Exposure to global engineering teams and enterprise-scale AI transformation projects Health, insurance, and wellness benefits (as per policy and location) Learning and development support for advanced AI and data engineering skills Access to modern cloud-native and AI-first technology stacks Collaborative, engineering-driven culture focused on innovation and impact. ## 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 Data Engineer with AI experience. Skills: Data Engineering, AI Infrastructure, LLM Systems, Agentic Systems. Build batch data pipelines. 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Design end-to-end data architectures, Architect and implement AI/ML solutions, Collaborate with customers' technical and business stakeholders, Define data strategies, roadmaps, and governance frameworks, Lead technical workstreams within ProServe engagements, Mentor junior architects and consultants, Develop reusable assets, frameworks, and best practices, Partner with AWS account teams, solution architects, and, Identify and shape new customer opportunities, Contribute to thought leadership, Stay current with emerging AWS services and industry", "teamCollaboration" : "Customer stakeholders; AWS account teams; Solution architects; Specialist teams", "projectManagementSkills" : [ "Roadmap development" ], "domainKnowledge" : "Manufacturing; Semiconductor industry; Data platforms; Analytics solutions; AI/ML workloads; Data lakes; Data mesh; Lakehouses; Streaming analytics; Enterprise data warehouses; Industry 4.0; Smart Manufacturing; IoT; Digital twin; Edge-to-cloud architectures; OT/IT convergence; Generative AI architectures; RAG patterns; Foundation model fine-tuning; AI agents", "domainList" : [ "manufacturing", "semiconductor-industry", "data-platforms", "analytics-solutions", "ai-ml-workloads", "data-lakes", "data-mesh", "lakehouses", "streaming-analytics", "enterprise-data-warehouses", "industry-4-0", "smart-manufacturing", "iot", "digital-twin", "edge-to-cloud-architectures", "ot-it-convergence", "generative-ai-architectures", "rag-patterns", "foundation-model-fine-tuning", "ai-agents" ], "domainSpecificKnowledge" : [ "Manufacturing", "Semiconductor industry", "Data platforms", "Analytics solutions", "AI/ML workloads", "Data lakes", "Data mesh", "Lakehouses", "Streaming analytics", "Enterprise data warehouses", "Industry 4.0", "Smart Manufacturing", "IoT", "Digital twin", "Edge-to-cloud architectures", "OT/IT convergence", "Generative AI architectures", "RAG patterns", "Foundation model fine-tuning", "AI agents" ], "toolProficiency" : [ "Amazon S3", "AWS Glue", "Amazon Redshift", "Amazon EMR", "Amazon Kinesis", "AWS Lake Formation", "Amazon SageMaker", "Amazon Bedrock" ], "communicationSkills" : "Technical concepts; Customer presentations", "documentationSkills" : "Whitepapers; Blog posts; Reference architectures", "continuousLearning" : "Emerging AWS services; Industry trends", "problemSolvingSkills" : "Root cause analysis", "outcomesObjectives" : "Unlock business value from data assets; Accelerate cloud adoption journey", "qualificationsBasic" : "Experience conveying complex technical concepts, Bachelor's degree or above in computer science, computer engineering, or related field, Bachelor's degree and 1+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience, 8+ years of experience in data engineering, data architecture, or cloud architecture, 5+ years hands-on designing and implementing data solutions on AWS or other major cloud platforms, Deep expertise in data platform technologies, Proficiency in Python, SQL, Spark, or Scala, Fluency in Mandarin Chinese and English", "qualificationsPreferred" : "Experience with large scale IT/digital business transformation or migration programs, Domain expertise in manufacturing and/or semiconductor industries, Experience with Industry 4.0 / Smart Manufacturing initiatives, Experience with generative AI architectures, Familiarity with data privacy and compliance requirements in the Taiwan market", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking an experienced Data and AI Cloud Architect to join our AWS Professional Services team in Taiwan. In this role, you will work directly with enterprise customers — particularly in the manufacturing and semiconductor industries — to design and implement modern data platforms, analytics solutions, and AI/ML workloads on AWS. You will serve as a trusted technical advisor, helping customers accelerate their cloud adoption journey and unlock business value from their data assets. Key job responsibilities Key Responsibilities - Lead the architecture design and delivery of data and AI solutions on AWS for strategic customers in Taiwan, with a focus on manufacturing and semiconductor verticals - Design end-to-end data architectures including data lakes, data mesh, lakehouses, streaming analytics, and enterprise data warehouses using AWS services (e.g., Amazon S3, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Lake Formation) - Architect and implement AI/ML solutions leveraging Amazon SageMaker, Amazon Bedrock, and other AWS AI services to address industry-specific use cases (predictive maintenance, yield optimization, defect detection, supply chain optimization) - Collaborate with customers' technical and business stakeholders to define data strategies, roadmaps, and governance frameworks - Lead technical workstreams within ProServe engagements, mentoring junior architects and consultants - Develop reusable assets, frameworks, and best practices for Data & AI solution delivery within the manufacturing and semiconductor domains - Partner with AWS account teams, solution architects, and specialist teams to identify and shape new customer opportunities - Contribute to thought leadership through whitepapers, blog posts, reference architectures, and customer presentations - Stay current with emerging AWS services and industry trends in data engineering, analytics, and generative AI About the team AWS Professional Services works with enterprise customers and partners to help them realize their desired business outcomes through cloud adoption. Our team assists customers in achieving the greatest value from AWS by providing guidance, best practices, and hands-on delivery support throughout their cloud journey. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Basic Qualifications: - Experience conveying complex technical concepts to both technical and business audiences - Bachelor's degree or above in computer science, computer engineering, or related field, or Bachelor's degree and 1+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience - 8+ years of experience in data engineering, data architecture, or cloud architecture, with 5+ years hands-on designing and implementing data solutions on AWS or other major cloud platforms - Deep expertise in data platform technologies: data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, and data governance, with proficiency in Python, SQL, Spark, or Scala - Fluency in Mandarin Chinese and English (written and verbal) Preferred Qualifications: - Experience with large scale IT/digital/business transformation or migration programs in a customer facing role - Domain expertise in manufacturing and/or semiconductor industries — understanding of fab operations, MES/ERP integration, equipment health monitoring, yield management, process control (SPC/FDC), supply chain digitization, and semiconductor-specific data challenges (high-volume time-series data, wafer-level analytics, APC, predictive maintenance) - Experience with Industry 4.0 / Smart Manufacturing initiatives including IoT, digital twin, edge-to-cloud architectures, and OT/IT convergence for industrial data integration - Experience with generative AI architectures including RAG patterns, foundation model fine-tuning, and AI agents - Familiarity with data privacy and compliance requirements in the Taiwan market 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 and AI Architect, Professional Services - Taiwan at Amazon Web Services Taiwan Limited. Skills: Data Architecture, AI/ML, AWS. Lead architecture design and delivery of data and. 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Work with engineering; Collaborate with product; Work with design; Collaborate with product marketing; Hold ground respectfully", "projectManagementSkills" : [ "Roadmap decisions" ], "domainKnowledge" : "Banking infrastructure; Payments; Fintech; Attach rate; Payment rails; KYC; AP workflows; Pre-authorized payments; Balance/deposit metrics; Churn dynamics", "domainList" : [ "banking-infrastructure", "payments", "fintech", "attach-rate", "payment-rails", "kyc", "ap-workflows", "pre-authorized-payments", "balance-deposit-metrics", "churn-dynamics" ], "domainSpecificKnowledge" : [ "Banking infrastructure", "Payments", "Fintech", "Attach rate", "Payment rails", "KYC", "AP workflows", "Pre-authorized payments", "Balance/deposit metrics", "Churn dynamics" ], "toolProficiency" : [ "Metabase", "Looker", "Tableau", "Sigma", "Snowflake", "Dbt Cloud" ], "communicationSkills" : "Translate roadmap decisions; Present findings; Respectful disagreement", "problemSolvingSkills" : "Debug ambiguous numbers; Root cause analysis", "qualificationsBasic" : "2-4+ years product analytics, SQL proficiency, Dbt-comfortable, Metabase, Looker, Tableau, Sigma experience", "qualificationsPreferred" : "PhD preferred, Fintech familiarity, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT FLOAT Float is on a mission to simplify finance for Canadian businesses, empowering them to eliminate complexity and unlock new opportunities. Through our innovative platform, Float enables businesses to streamline financial operations and optimize cash flow, so they can focus on what matters most: growth. As one of Canada’s fastest growing companies https://www.theglobeandmail.com/business/rob-magazine/top-growing-companies/article-ranking-canadas-top-growing-companies-of-2024/ and top-rated startups in 2025 https://www.linkedin.com/posts/floatfinancial_were-proud-to-share-that-float-has-been-activity-7387093684720300032-2DDz/, 2024 https://www.linkedin.com/pulse/linkedin-top-startups-2024-15-canadian-companies-rise-linkedin-news-llihe/ and 2023 https://lnkd.in/TSU23CA, Float is customer-obsessed, passionate and entrepreneurial, with a team that includes leaders from Uber, Stripe, Shopify, Top Hat, Ada, Doordash, Snowflake, and Wealthsimple. At Float, everyone is an owner, bringing their unique perspective to our team and product. Your voice is important, and we take having a culture based on feedback seriously. We openly share our thoughts and differing opinions so we can continue to improve. We do our best to keep our decision-making decentralized so that all team members feel ownership in our success. OUR PRODUCT Float is Canada's complete business finance platform, combining modern financial services and software to help businesses spend, save, and grow. Trusted by 6000+ Canadian companies, Float provides high-limit corporate cards, automated expense management, next-day bill payments, high-yield accounts and fast, friendly support—all built in Canada, for Canada. Float is backed by world-class venture and fintech investors, including Growth Equity at Goldman Sachs Alternatives and OMERS Ventures, partners behind our $70 million Series B raise https://floatfinancial.com/we-raised-70-million-to-fix-canadas-business-banking-problem/. Our team is a collection of ambitious, collaborative and mission-driven people from all walks of life but with one goal: helping Canadian companies not just survive but thrive. And we’re looking for bold innovators to help shape the future of business finance in Canada. AI USE IN OUR HIRING PROCESS We use technology, including artificial intelligence (AI), to support parts of our hiring process. This may include AI-assisted scheduling and candidate communications, and AI-generated interview notes, guides or summaries to help our team focus on the conversation. All hiring decisions are made by our hiring team. ABOUT THE ROLE Float is building the financial operating system for Canadian businesses — corporate cards, business bank accounts, bill payments, all in one place. Reporting to the Head of Data, this role is embedded inside the product teams behind two of those core pillars: banking infrastructure and payments. Both are high-complexity, high-stakes areas that generate a dense mix of financial, behavioral, and operational data. This role owns that data layer. You're building cohorts before anyone asks, designing measurement frameworks before features go to engineering, and debugging numbers to the source — pipeline issue, definition mismatch, or real product signal. You're also someone who uses AI to move faster without losing rigour. Getting useful outputs from a model means knowing the business and data well enough to give it the right context — that's part of the job too. WHAT YOU'LL BE DOING - Define what needs to be measured before features ship and support the instrumentation to measure it. You translate roadmap decisions into measurement requirements. - Design and get broad alignment on measurement frameworks before features go to engineering — hypothesis, cohorts, success criteria. - Design and analyze experiments - structure A/B tests for product changes. Define the hypothesis, select the right unit of randomization, size the experiment for sufficient power and interpret results with statistical rigour - Own the metrics and dashboards for Banking and Payments. Every number is traceable to a reliable dbt model. You keep them accurate. - Own data quality in your product area — audit dbt models, write clear briefs for analytics engineering, flag gaps before they become problems. - Run cohort and retention analysis natively — activation sequences, behavioral funnels, leading vs. lagging indicators. Diagnose which lever moves the number, not just what happened. - Debug ambiguous numbers to the source — pipeline issue, definition mismatch, or real product signal. You close the loop. - Write expert SQL and bring statistical rigour — cohort construction, retention calculations, confidence intervals, significance testing. You know when you have enough signal to act. - Use AI as a multiplier — accelerate analysis, generate first-pass SQL, and pressure-test hypotheses faster than you could alone. You know how to give a model the business and data context that makes its outputs impactful. - Take your share of ad-hoc requests on rotation — owning your product area gives the broader data team meaningful breathing room. WHAT SUCCESS LOOKS LIKE - Get Embedded: Both team leads treat you as the owner of their data layer. KPI definitions are agreed upon, documented, and tied to reliable dbt models. Gaps are flagged with a fix in motion. - Build the Measurement Layer: Features ship with measurement frameworks designed upfront. Dashboards for the core banking and payments metrics are clean, trusted, and traceable. - Drive Product Evidence: Product decisions are shaped by your analysis before they are made. When a team lead is asked by leadership whether a feature is landing, they already know — because you’ve built the infrastructure that makes the question answerable. WHAT WE'RE LOOKING FOR - Product analytics depth — you've been embedded in a product team, own activation funnels and cohort retention natively, and know how to instrument a feature before it ships. - Experimentation and measurement design — you design A/B tests and quasi-experiments from the ground up: hypothesis, randomization unit, sample size and power calculations, guardrail metrics, and holdout design. You build pre/post and diff-in-diff analyses where randomization isn't feasible, and you know how to communicate the difference in confidence between the two - Data layer ownership — you're the DRI for data quality in your product area: auditing dbt models, writing briefs for analytics engineering, and debugging ambiguous numbers to the source. - Expert-level SQL — you build complex multi-step queries across large behavioral datasets, optimize for performance, and explain the logic to non-technical stakeholders. - Statistical reasoning — you understand distributions, confidence intervals, significance testing, and sample size constraints. You design for confounders, know when you have enough signal, and communicate uncertainty in plain language. - Data modeling literacy — you translate business logic into data requirements, specify the grain a table needs, and have informed opinions on how metrics get structured in dbt. - Comfort with imperfect data — you make a reasoned call, state your confidence level, and give stakeholders something actionable rather than waiting for clean infrastructure. - Stakeholder fluency — you work effectively across Product, Design, Engineering, and Product Marketing, and hold your ground respectfully when data contradicts what the team wants to believe. - AI as an accelerator — you've used LLMs to write SQL, draft frameworks, or structure analysis, and you know where they're reliable and where they need guardrails. - 2–4+ years in product analytics, ideally embedded in a product team at a high-growth fintech or SaaS company. - BI tool experience — Metabase, Looker, Tableau, Sigma, or similar. - dbt-comfortable (reading models, understanding lineage) with Snowflake or a comparable cloud warehouse. - Fintech familiarity — attach rate, payment rails, KYC, AP workflows, pre-authorized payments, balance/deposit metrics, churn dynamics — is a meaningful differentiator. OUR HIRING PHILOSOPHY We hire for character, curiosity, and learning velocity before credentials. Titles matter less than impact, and every hire is expected to raise the bar for Float as a whole. WHY YOU SHOULD JOIN - Work at one of Canada's fastest-growing fintech companies - Make a real impact in a high-autonomy, high-growth role - Collaborate with an ambitious and supportive team - Competitive compensation, equity options, and benefits - Hybrid work model – we are based in Toronto with in-office days for connection and collaboration - Enjoy catered team lunches every Tuesday, Wednesday and Thursday - Bring your pup to our dog-friendly office - Thrive in a high-trust, high-performance culture where your work truly matters IN SHORT At Float, you’ll thrive if you’re bold, curious, and eager to make a real impact. We're building something special—and having a lot of fun along the way. If you’re excited to build, grow, and win together, we’d love to meet you. We’re committed to building a workplace that’s welcoming and accessible for everyone. If you need any accommodations during the hiring process or once you join Float, just let us know! You can reach out to Vic https://www.linkedin.com/in/victoria-boult-b21b2053/ (victoria@floatfinancial.com), and we’ll work with you to make sure you have what you need to succeed.", "summaryDescription" : "Data Analyst, Product (Banking and Payments) at Float. Skills: Product analytics, Data engineering, Machine learning, Business intelligence. Define measurement requirements. 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Kraków, Poland", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "SQL, Python, Pandas, NumPy, SciPy, PySpark", "professionalSkills" : [ "Data wrangling", "Data transformation", "ETL processes", "Analytical skills", "Problem-solving skills", "Critical-thinking skills", "Stakeholder management" ], "hardSkillsList" : [ "Data analysis", "Machine learning models" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Machine learning models", "level" : "intermediate" } ], "majorSkills" : "Data analysis, Machine learning, ETL", "majorSkillsList" : [ "Data analysis", "Machine learning", "ETL" ], "coreResponsibilities" : "Support development of models, Prepare data from sources, Clean datasets, Transform datasets, Validate datasets, Analyze datasets, Design ETL pipelines, Develop ETL pipelines, Optimize ETL pipelines, Work with large databases, Extract data, Manage data, Collaborate with teams, Partner with stakeholders, Understand requirements, Translate requirements, Identify data quality issues, Implement solutions, Improve data accuracy, Improve data consistency, Improve data accessibility, Contribute to process improvement, Support knowledge sharing, Support best practices", "teamCollaboration" : "Cross-functional teams; Data scientists; Model developers; Business stakeholders; International stakeholders", "domainKnowledge" : "Financial services; Machine learning models", "domainList" : [ "financial-services", "machine-learning-models" ], "domainSpecificKnowledge" : [ "Financial services", "Machine learning models" ], "communicationSkills" : "Stakeholder management", "continuousLearning" : "Professional development; Learning platforms; Professional certifications", "problemSolvingSkills" : "Analytical skills; Problem-solving skills; Critical-thinking skills", "qualificationsBasic" : "5+ years experience, Fluency in French (B2+), Fluency in English, SQL proficiency, Python proficiency, Bachelor's degree", "qualificationsPreferred" : "Banking domain experience, Financial services domain experience, Experience supporting machine learning, Experience supporting advanced analytics, Knowledge of cloud-based data platforms, Knowledge of modern data architectures, Experience working in Agile environments, Exposure to data governance, Exposure to data quality frameworks, PhD preferred", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Senior Data Analyst (Financial Services) with French Location: Warsaw or Kraków (Hybrid 1-2 office days per month) About Capco At Capco Poland, we're not just another consultancy—we're the dynamic force driving digital transformation in the financial world. As a global leader in technology and management consulting, we help clients tackle complex challenges across banking, payments, capital markets, wealth, and asset management. Our culture is fast-paced, flexible, and entrepreneurial. We move quickly, think creatively, and put people at the center of everything we do. We're passionate about delivering value to our clients while creating opportunities for our people to grow and thrive. We're proud to be: Leaders in banking, payments, capital markets, wealth, and asset management consulting Champions of an agile, innovative, and collaborative work environment Committed to attracting and developing exceptional talent The Role We are looking for an experienced Senior Data Analyst with French to join a high-performing team supporting the development of advanced machine learning models within a global financial services environment. In this role, you will work closely with data scientists, model developers, and business stakeholders to deliver high-quality data solutions that power analytical and modeling initiatives. You will be responsible for sourcing, transforming, analyzing, and preparing large-scale datasets while contributing to the design and implementation of robust ETL processes. As a senior member of the team, you will also play a key role in driving analytical initiatives, collaborating with international stakeholders, and ensuring data quality and consistency across complex environments. Key Responsibilities Support the development of advanced financial machine learning models by sourcing, aggregating, and preparing data from multiple internal and external sources. Clean, transform, validate, and analyze complex datasets to ensure high-quality inputs for modeling activities. Design, develop, and optimize ETL pipelines to streamline data ingestion and processing workflows. Work with large-scale databases and distributed data environments to extract and manage data efficiently. Collaborate with cross-functional teams including model developers, data scientists, and business stakeholders. Partner with business stakeholders to understand requirements and translate them into data-driven solutions. Identify data quality issues and implement solutions to improve data accuracy, consistency, and accessibility. Contribute to the continuous improvement of data management, reporting, and analytical processes. Support knowledge sharing and best practices across the wider data and analytics community. Skills & Experience 5+ years of experience as a Data Analyst, preferably within complex enterprise environments. Fluency in French (B2+) and English is required. Strong proficiency in SQL and Python, including: Pandas NumPy SciPy PySpark Solid understanding of data wrangling, data transformation, and ETL processes. Experience working with large and complex databases and distributed data environments. Strong analytical, problem-solving, and critical-thinking skills. Experience collaborating with business stakeholders and translating business requirements into analytical solutions. Ability to work independently and manage multiple priorities in a fast-paced environment. Excellent communication and stakeholder management skills. Detail-oriented, collaborative, and business-focused mindset. Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. Nice to Have Banking or financial services domain experience. Experience supporting machine learning or advanced analytics initiatives. Knowledge of cloud-based data platforms and modern data architectures. Experience working in Agile environments. Exposure to data governance and data quality frameworks. What We Offer Flexible collaboration model based on a B2B contract. Opportunity to work on challenging projects within the financial services sector. Exposure to modern data, analytics, and machine learning initiatives. Collaborative and supportive team environment. Access to professional development opportunities and a global network of experts. Hybrid working model. Access to employee benefits packages, including private medical care and life insurance. Access to learning platforms and professional certifications. Recruitment Process Screening Call with a Recruiter Capco Hiring Manager Interview Client Interview Feedback / Offer Joining Capco means joining an organization that is committed to an inclusive working environment where you're encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. #LI-HYBRID", "summaryDescription" : "Senior Data Analyst with French at Capco. Skills: Data analysis, Machine learning, ETL. Support development of models. 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Austin:1117 Trinity St (320TX-4002)
1117 Trinity St
Austin, 78701-1919

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Ensure departmental processes are transparent; Ensure departmental processes are professional; Acquisitions of program services for the State", "qualificationsBasic" : "Five years of experience in oversight and direction of an agency or in strategic planning and policy development and implementation, Two years of experience in administrative management or supervisory capacity, Two years of experience in data collection and analysis, One year experience in management and direction of staff relevant to data collection and analysis, Experience with state data reporting and analysis", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Data Analysis and Quality Assurance (DAQA) Director Who We Are: Texas Workforce Commission connects people with careers across the state. We are based in Austin on the east side of the Texas State Capitol, in the Business Operations Division located at 1117 Trinity Street in Austin. We're a Family Friendly Certified Workplace with great work-life balance, competitive salaries, extensive opportunities for training and development, and fantastic benefits. TWC is not considering applications from individuals who require sponsorship for an employment visa, including those with H1B visas or those currently on student or postgraduate visas. You must be a Texas resident to work for the Texas Workforce Commission or willing to relocate to Texas. Who You Are: A self-starting, motivated, collaborative problem solver who understands the value of data analysis in measurement of procurement and contract related activities for the Procurement and Contract Services Department. You should share our department’s mission to provide excellent customer service and ensure that departmental processes are impartial, transparent, and professional. You should be innovative and open to new ideas to streamline existing processes. We strive to ensure that acquisitions of program services are conducted with the best outcome for the State in mind. What you Will Do: The Data Analysis and Quality Assurance (DAQA) Director: -Directs data reporting and analysis activities. -Develops and implements techniques for analyzing and reporting data in meaningful ways and remains compliant with state and federal rules and regulations. -Develops and establishes goals and objectives consistent with the agency policy and procedure. -Provides direction, guidance, and assistance in developing reports and collecting data related to contracts and procurement. -Reviews and approves reports, data collection and analysis, and ensures accuracy and that quality reports are distributed. -Reviews guidelines, procedures, rules, and regulations; and monitors compliance related to contract and procurement databases. -Makes recommendations to improve data collection and analysis. -Plans, develops, and approves schedules, priorities, and standards for achieving goals. -Reviews results of special investigations, internal audits, research studies, forecasts, and modeling exercises to provide direction and guidance. -Performs advanced (senior-level) managerial work providing direction and guidance in strategic operations and planning. Works under minimal supervision, with extensive latitude for the use of initiative and independent judgment. You Will be Trusted To: -Establish goals and objectives. -Respond to audit requests from internal and external entities. -Develop guidelines, procedures, policies, rules, and regulations. -Develop schedules, priorities, and standards for achieving established goals. -Coordinate and evaluate data collection, reporting, and quality. -Develop and evaluate data reports and policies and procedures for producing quality reports and maintaining data integrity. -Plan, assign, and supervise the work of others. -Work under limited supervision, with considerable latitude for the use of initiative and independent judgment. -Performs other duties as assigned. You Qualify With: -Five years of full-time experience in the oversight and direction of an agency program; or in strategic planning and policy development and implementation, two years of which must have been in an administrative management or supervisory capacity. -Relevant academic credits may be applied toward experience qualifications for this position. You Are a Great Fit With: -A minimum of two years’ experience in data collection and analysis. -One year experience in the management and direction of staff relevant to data collection and analysis. -Experience with state data reporting and analysis. You Gain: -A Family Friendly Certified Workplace. -Competitive starting salary: $9,166.67 to $9,583.34/month, depending on experience -Defined Retirement Benefit Plan -Optional 401(k) and 457 accounts -Medical Insurance -Paid time off, including time for vacation, sick and family care leave -Additional benefits for active employees can be found at https://www.ers.texas.gov/Active-Employees/Health-Benefits. VETERANS: Use your military skills to qualify for this position or other jobs! Go to www.texasskillstowork.com to translate your military work experience and training courses into civilian job terms, qualifications, and skill sets. Also, you can compare this position to military occupations (MOS) at the Texas State Auditor's Office by pasting this link into your browser: https://hr.sao.texas.gov/Compensation/MilitaryCrosswalk/MOSC_ProgramManagement.pdf HOW TO APPLY: To be considered, please complete a State of Texas Application for Employment and apply online at www.workintexas.com or on Taleo ( Job Search ). TWC is not considering applications from individuals who require sponsorship for an employment visa, including those with H1B visas or those currently on student or postgraduate visas In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire. A position utilizing this classification will be designated as security sensitive according to the Texas Labor Code, Section 301.042. United States-Texas-Austin", "summaryDescription" : "Data Analysis and Quality Assurance Director at Texas Workforce Commission. Skills: Data analysis, Quality assurance, Data engineering, Machine learning. Direct data reporting and analysis activities. 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Engineering; Product Marketing; Head of Data", "projectManagementSkills" : [ "Roadmap decisions" ], "domainKnowledge" : "Banking infrastructure; Payments; Fintech; Attach rate; Payment rails; KYC; AP workflows; Pre-authorized payments; Balance/deposit metrics; Churn dynamics", "domainList" : [ "banking-infrastructure", "payments", "fintech", "attach-rate", "payment-rails", "kyc", "ap-workflows", "pre-authorized-payments", "balance-deposit-metrics", "churn-dynamics" ], "domainSpecificKnowledge" : [ "Banking infrastructure", "Payments", "Fintech", "Attach rate", "Payment rails", "KYC", "AP workflows", "Pre-authorized payments", "Balance/deposit metrics", "Churn dynamics" ], "toolProficiency" : [ "Metabase", "Looker", "Tableau", "Sigma" ], "communicationSkills" : "Hold ground respectfully", "problemSolvingSkills" : "Debug ambiguous numbers", "qualificationsBasic" : "2-4+ years product analytics, SQL proficiency, Dbt-comfortable, Snowflake or comparable warehouse", "qualificationsPreferred" : "PhD preferred, Fintech familiarity", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT FLOAT Float is on a mission to simplify finance for Canadian businesses, empowering them to eliminate complexity and unlock new opportunities. Through our innovative platform, Float enables businesses to streamline financial operations and optimize cash flow, so they can focus on what matters most: growth. As one of Canada’s fastest growing companies https://www.theglobeandmail.com/business/rob-magazine/top-growing-companies/article-ranking-canadas-top-growing-companies-of-2024/ and top-rated startups in 2025 https://www.linkedin.com/posts/floatfinancial_were-proud-to-share-that-float-has-been-activity-7387093684720300032-2DDz/, 2024 https://www.linkedin.com/pulse/linkedin-top-startups-2024-15-canadian-companies-rise-linkedin-news-llihe/ and 2023 https://lnkd.in/TSU23CA, Float is customer-obsessed, passionate and entrepreneurial, with a team that includes leaders from Uber, Stripe, Shopify, Top Hat, Ada, Doordash, Snowflake, and Wealthsimple. At Float, everyone is an owner, bringing their unique perspective to our team and product. Your voice is important, and we take having a culture based on feedback seriously. We openly share our thoughts and differing opinions so we can continue to improve. We do our best to keep our decision-making decentralized so that all team members feel ownership in our success. OUR PRODUCT Float is Canada's complete business finance platform, combining modern financial services and software to help businesses spend, save, and grow. Trusted by 6000+ Canadian companies, Float provides high-limit corporate cards, automated expense management, next-day bill payments, high-yield accounts and fast, friendly support—all built in Canada, for Canada. Float is backed by world-class venture and fintech investors, including Growth Equity at Goldman Sachs Alternatives and OMERS Ventures, partners behind our $70 million Series B raise https://floatfinancial.com/we-raised-70-million-to-fix-canadas-business-banking-problem/. Our team is a collection of ambitious, collaborative and mission-driven people from all walks of life but with one goal: helping Canadian companies not just survive but thrive. And we’re looking for bold innovators to help shape the future of business finance in Canada. AI USE IN OUR HIRING PROCESS We use technology, including artificial intelligence (AI), to support parts of our hiring process. This may include AI-assisted scheduling and candidate communications, and AI-generated interview notes, guides or summaries to help our team focus on the conversation. All hiring decisions are made by our hiring team. ABOUT THE ROLE Float is building the financial operating system for Canadian businesses — corporate cards, business bank accounts, bill payments, all in one place. Reporting to the Head of Data, this role is embedded inside the product teams behind two of those core pillars: banking infrastructure and payments. Both are high-complexity, high-stakes areas that generate a dense mix of financial, behavioral, and operational data. This role owns that data layer. You're building cohorts before anyone asks, designing measurement frameworks before features go to engineering, and debugging numbers to the source — pipeline issue, definition mismatch, or real product signal. You're also someone who uses AI to move faster without losing rigour. Getting useful outputs from a model means knowing the business and data well enough to give it the right context — that's part of the job too. WHAT YOU'LL BE DOING - Define what needs to be measured before features ship and support the instrumentation to measure it. You translate roadmap decisions into measurement requirements. - Design and get broad alignment on measurement frameworks before features go to engineering — hypothesis, cohorts, success criteria. - Design and analyze experiments - structure A/B tests for product changes. Define the hypothesis, select the right unit of randomization, size the experiment for sufficient power and interpret results with statistical rigour - Own the metrics and dashboards for Banking and Payments. Every number is traceable to a reliable dbt model. You keep them accurate. - Own data quality in your product area — audit dbt models, write clear briefs for analytics engineering, flag gaps before they become problems. - Run cohort and retention analysis natively — activation sequences, behavioral funnels, leading vs. lagging indicators. Diagnose which lever moves the number, not just what happened. - Debug ambiguous numbers to the source — pipeline issue, definition mismatch, or real product signal. You close the loop. - Write expert SQL and bring statistical rigour — cohort construction, retention calculations, confidence intervals, significance testing. You know when you have enough signal to act. - Use AI as a multiplier — accelerate analysis, generate first-pass SQL, and pressure-test hypotheses faster than you could alone. You know how to give a model the business and data context that makes its outputs impactful. - Take your share of ad-hoc requests on rotation — owning your product area gives the broader data team meaningful breathing room. WHAT SUCCESS LOOKS LIKE - Get Embedded: Both team leads treat you as the owner of their data layer. KPI definitions are agreed upon, documented, and tied to reliable dbt models. Gaps are flagged with a fix in motion. - Build the Measurement Layer: Features ship with measurement frameworks designed upfront. Dashboards for the core banking and payments metrics are clean, trusted, and traceable. - Drive Product Evidence: Product decisions are shaped by your analysis before they are made. When a team lead is asked by leadership whether a feature is landing, they already know — because you’ve built the infrastructure that makes the question answerable. WHAT WE'RE LOOKING FOR - Product analytics depth — you've been embedded in a product team, own activation funnels and cohort retention natively, and know how to instrument a feature before it ships. - Experimentation and measurement design — you design A/B tests and quasi-experiments from the ground up: hypothesis, randomization unit, sample size and power calculations, guardrail metrics, and holdout design. You build pre/post and diff-in-diff analyses where randomization isn't feasible, and you know how to communicate the difference in confidence between the two - Data layer ownership — you're the DRI for data quality in your product area: auditing dbt models, writing briefs for analytics engineering, and debugging ambiguous numbers to the source. - Expert-level SQL — you build complex multi-step queries across large behavioral datasets, optimize for performance, and explain the logic to non-technical stakeholders. - Statistical reasoning — you understand distributions, confidence intervals, significance testing, and sample size constraints. You design for confounders, know when you have enough signal, and communicate uncertainty in plain language. - Data modeling literacy — you translate business logic into data requirements, specify the grain a table needs, and have informed opinions on how metrics get structured in dbt. - Comfort with imperfect data — you make a reasoned call, state your confidence level, and give stakeholders something actionable rather than waiting for clean infrastructure. - Stakeholder fluency — you work effectively across Product, Design, Engineering, and Product Marketing, and hold your ground respectfully when data contradicts what the team wants to believe. - AI as an accelerator — you've used LLMs to write SQL, draft frameworks, or structure analysis, and you know where they're reliable and where they need guardrails. - 2–4+ years in product analytics, ideally embedded in a product team at a high-growth fintech or SaaS company. - BI tool experience — Metabase, Looker, Tableau, Sigma, or similar. - dbt-comfortable (reading models, understanding lineage) with Snowflake or a comparable cloud warehouse. - Fintech familiarity — attach rate, payment rails, KYC, AP workflows, pre-authorized payments, balance/deposit metrics, churn dynamics — is a meaningful differentiator. OUR HIRING PHILOSOPHY We hire for character, curiosity, and learning velocity before credentials. Titles matter less than impact, and every hire is expected to raise the bar for Float as a whole. WHY YOU SHOULD JOIN - Work at one of Canada's fastest-growing fintech companies - Make a real impact in a high-autonomy, high-growth role - Collaborate with an ambitious and supportive team - Competitive compensation, equity options, and benefits - Hybrid work model – we are based in Toronto with in-office days for connection and collaboration - Enjoy catered team lunches every Tuesday, Wednesday and Thursday - Bring your pup to our dog-friendly office - Thrive in a high-trust, high-performance culture where your work truly matters IN SHORT At Float, you’ll thrive if you’re bold, curious, and eager to make a real impact. We're building something special—and having a lot of fun along the way. If you’re excited to build, grow, and win together, we’d love to meet you. We’re committed to building a workplace that’s welcoming and accessible for everyone. If you need any accommodations during the hiring process or once you join Float, just let us know! You can reach out to Vic https://www.linkedin.com/in/victoria-boult-b21b2053/ (victoria@floatfinancial.com), and we’ll work with you to make sure you have what you need to succeed.", "summaryDescription" : "Data Analyst, Product (Banking and Payments) at Float. Skills: Product analytics, Data quality, Experimentation. Define measurement needs. Support instrumentation", "createdAt" : "2026-06-14T04:38:39.979", "lastUpdated" : "2026-06-15T09:15:39.904", "ingestTimestamp" : "2026-06-14T04:38:39.979", "mongoId" : "6a2ca07874d8ee00a09a24fe", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Statistical analysis", "A/B testing", "Hypothesis testing", "Confidence intervals", "Significance testing", "Learning velocity", "Product analytics", "Data quality", "Experimentation", "Measurement frameworks", "Experiment design", "Data quality audit", "Cohort analysis", "Retention analysis", "Statistical rigor", "Roadmap decisions", "Banking infrastructure", "Payments", "Fintech", "Attach rate", "Payment rails", "KYC", "AP workflows", "Pre-authorized payments", "Balance/deposit metrics", "Churn dynamics", "Metabase", "Looker", "Tableau", "Sigma" ], "skillCount" : 30, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "69fda4e74c40e2acd1b99b8b", "title" : "Data Engineer, AIR DABI (Data Analytics and Business Intelligence)", "company" : "Amazon.com Services LLC", "industry" : "Database Administration, Data Engineering, transportation and logistics", "salary" : { "min" : 101000.0, "max" : 160000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Bellevue, Washington, USA", "locations" : [ "Bellevue, Washington, USA" ], "timestamp" : "2026-06-15T03:34:52.489", "fingerprint" : "f5761f1a8ae6ba0cd457533ce16979448f146e28d2ca815c6657d28a8854a628", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10411675/apply", "externalId" : "93b92467-2d61-4650-83f6-05d9f36c35e2", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bellevue", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6144219,-122.1923370" } ], "locationText" : "Bellevue, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala, Python, KornShell, AWS, Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, IAM, Hadoop, Apache Spark, GenAI, LLM", "professionalSkills" : [ "Data modeling", "Database architecture", "Business analysis", "Data transformation", "Data integration", "Data architecture", "Generative AI" ], "hardSkillsList" : [ "ETL processes", "Data integration", "Data pipelines", "Data modeling", "Database management", "Data warehousing", "Data transformation", "Data analysis" ], "hardSkills" : [ { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "Data integration", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Database management", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "majorSkills" : "Data Engineering, ETL/ELT, AWS, Generative AI", "majorSkillsList" : [ "Data Engineering", "ETL/ELT", "AWS", "Generative AI" ], "coreResponsibilities" : "Design ETL/ELT processes, Implement ETL/ELT processes, Create data integration solutions, Transform business requirements, Develop data pipelines, Maintain data pipelines, Identify data infrastructure challenges, Resolve data infrastructure challenges, Collaborate with cross-functional teams, Drive data-driven decision-making, Contribute to GenAI infrastructure development, Contribute to data foundations development, Design data architectures, Implement data architectures, Support generative AI applications, Support LLM workflows, Leverage GenAI tools, Accelerate development, Accelerate testing", "teamCollaboration" : "Cross-functional teams; Analysts; Business Intelligence Engineers; Data Scientists; SDEs; Business teams", "domainKnowledge" : "Data warehouse environment; Global logistics; Air transportation network; Generative AI applications; LLM workflows", "domainList" : [ "data-warehouse-environment", "global-logistics", "air-transportation-network", "generative-ai-applications", "llm-workflows" ], "domainSpecificKnowledge" : [ "Data warehouse environment", "Global logistics", "Air transportation network", "Generative AI applications", "LLM workflows" ], "toolProficiency" : [ "AWS", "Redshift", "S3", "AWS Glue", "EMR", "Kinesis", "FireHose", "Lambda", "IAM", "Hadoop", "Apache Spark", "Amazon Q" ], "innovationCreativity" : "Technical innovation", "problemSolvingSkills" : "Problem-solving", "qualificationsBasic" : "2+ years data engineering experience, Data modeling experience, Warehousing experience, Building ETL pipelines experience, SQL experience, PL/SQL experience, DDL experience, MDX experience, HiveQL experience, SparkSQL experience, Scala experience, Python experience, KornShell experience, GenAI/LLM tools familiarity", "qualificationsPreferred" : "Data engineer experience, Software engineer experience, Business intelligence engineer experience, Data scientist experience, Manipulating large datasets experience, Processing large datasets experience, Extracting value from large datasets experience, Hadoop experience, Apache Spark experience, Data warehouse technical architecture knowledge, Data warehouse infrastructure components knowledge, ETL knowledge, Reporting tools knowledge, Analytic tools knowledge, Data schema design knowledge, Data schema implementation knowledge, Normalization knowledge, Relational model knowledge, Dimensional model knowledge, Redshift experience, S3 experience, AWS Glue experience, EMR experience, Kinesis experience, FireHose experience, Lambda experience, IAM roles experience, IAM permissions experience, Informatica experience, ODI experience, SSIS experience, BODI experience, Datastage experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Do you want to join one of the most exciting teams at the world's most customer-centric company? Then come soar with Amazon Air! AIR's Data, Analytics and Business Intelligence (DABI) team aims to offer the data infrastructure and data applications, processes, and practices that enable the AIR business to leverage its capacity, speed, quality of service, and organic infrastructure to delight Amazon customers worldwide. We are looking for an experienced, innovative Data Engineer to work in a large and complex data warehouse environment. You should be passionate about working with disparate datasets and love bringing data together to answer business questions. You should have deep expertise in creating and managing datasets and a proven ability to translate data into meaningful insights through collaboration with Analysts, Business Intelligence Engineers, Data Scientists, SDEs, and business teams across the Amazon AIR organization. In this role, you will own end-to-end development of data engineering solutions to complex questions and play a critical role in strategic decision-making. The right candidate will possess excellent technical ability in relational database management systems and database architecture, solid business and communication skills, and the ability to work with business owners to develop and define key business questions, collaborate with external data vendors to onboard new datasets, and analyze data effectively. Key job responsibilities - Design and implement robust ETL/ELT processes using AWS big data technologies - Create scalable data integration solutions that transform complex business requirements into actionable insights - Develop and maintain high-performance data pipelines that support critical business intelligence needs - Proactively identify and resolve data infrastructure challenges to enhance system reliability - Collaborate with cross-functional teams to drive data-driven decision-making strategies - Contribute to the development and maintenance of AIR's GenAI infrastructure and data foundations - Design and implement data architectures that support generative AI applications and LLM workflows - Leverage GenAI tools (e.g., Amazon Q, coding assistants) to accelerate development and testing A day in the life Your day will be a dynamic blend of technical innovation and collaborative problem-solving. You'll dive into complex datasets, design elegant data pipelines, and work alongside cross-functional teams to unlock actionable intelligence that shapes the future of global logistics. About the team We are a passionate group of data professionals dedicated to transforming raw information into strategic insights. Our team thrives on collaboration, innovation, and a shared commitment to solving complex challenges that directly impact Amazon's global air transportation network. Basic Qualifications: - 2+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell) - Familiarity with leveraging GenAI/LLM tools to improve development productivity Preferred Qualifications: - Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets - Experience with big data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments - Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. 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, WA, Bellevue - 101,300.00 - 160,000.00 USD annually", "summaryDescription" : "Data Engineer, AIR DABI (Data Analytics and Business Intelligence) at Amazon.com Services LLC. Skills: Data Engineering, ETL/ELT, AWS, Generative AI. Design ETL/ELT processes. 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"Drive company-wide AI agenda, Scale AI initiatives into production systems, Own high-impact AI initiatives, Execute company operational transformation, Partner to embed AI capabilities, Serve as technical authority, Make architectural decisions, Oversee development of data platform, Transform internal knowledge base, Build systemic data architecture, Re-build data structures, Evolve connectivity pipelines, Deploy AI models efficiently, Lower cost-to-serve, Set tooling standards, Maintain technical quality guardrails, Establish engineering best practices, Support implementation of local solutions, Ensure platform support for specialists, Maintain ethical compliance, Ensure AI initiatives adhere to standards, Educate teams on AI use, Empower teams to scale AI, Provide structural frameworks, Partner with People and Operations, Champion organizational AI capability, Replace uncertainty with training loops, Convert specialists to power-users, Drive organizational change management, Drive literacy efforts, Reshape daily workflows, Shift company culture to AI-assisted operations", "teamCollaboration" : "Cross-functional teams; Product teams; Engineering teams; Operational leaders; Decentralized specialists; People functions; Operations functions", "domainKnowledge" : "AI-native platform; Knowledge management; Automation layer frameworks; ML orchestration frameworks; Distributed data systems; Corporate data platform; Unstructured information; Data privacy; Platform security; Ethical compliance; AI use productively; Organizational AI capability; Operational uncertainty; Automated solutions; Organizational change management; AI-assisted operations", "domainList" : [ "ai-native-platform", "knowledge-management", "automation-layer-frameworks", "ml-orchestration-frameworks", "distributed-data-systems", "corporate-data-platform", "unstructured-information", "data-privacy", "platform-security", "ethical-compliance", "ai-use-productively", "organizational-ai-capability", 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Enhance customer-facing product", "qualificationsBasic" : "5+ years of experience, SQL proficiency required", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "✨ ONE PLATFORM, A WHOLE WORLD OF OPPORTUNITY The best jobs are often restricted to a few wealthy cities, but talent exists everywhere. Oyster set out to change this by launching a global employment platform that enables companies to hire, pay, and support talent anywhere. We’re proof that a strong, engaged culture doesn't require an office. Since January 2020, Oyster has: \uD83C\uDF0F Built a distributed team of 400+ across 60+ countries \uD83D\uDC69‍\uD83D\uDCBB Featured in Forbes https://www.forbes.com/sites/laurabegleybloom/2024/01/25/work-from-home-or-anywhere-top-30-companies-for-remote-jobs-in-2024/ as #9 in FlexJobs Top 30 Companies for remote jobs \uD83C\uDF08 Formed a diverse leadership team and a workforce that’s 60% female \uD83C\uDFC6 Earned top employee engagement scores \uD83E\uDD84 Raised $286 million; valued at $1.2 billion \uD83D\uDC9A Achieved B Corp status in 2023 Our momentum shows the power of global employment, and we’re just getting started! If you want to help us drive change and work remotely, we’d love for you to apply! The Role While this position is posted in a specific location, all of Oyster’s positions are fully remote and you can work from home. Forever. To create the best experience for our new hire, this role requires you to be based within +3 / -7 UTC. As the Senior Director, Data Platform and AI, you will own the technical infrastructure and strategic direction that transforms Oyster into an AI-native global platform, decoupling scaling overhead from platform usage growth. Part of our Senior Tech Leadership Team, this highly specialized leadership role unites data platforms, product analytics pipelines, knowledge management, and advanced automation layer frameworks. You will lead the effort to transition AI initiatives from isolated experimentation into centralized systems. This is an organizational transformation role as much as a technical one. You will leverage AI to optimize our internal workflows, modernize our knowledge architecture, and directly enhance our customer-facing product. By building unified data structures and connectivity pipelines, you will directly lower our cost-to-serve and equip our global teams with the clear data and context they need to operate efficiently. Crucially, you will also educate and empower teams across Oyster to scale their own AI use productively. KEY RESPONSIBILITIES - Drive the company-wide AI agenda: scaling local AI initiatives into centralized production systems that create measurable business value. - Own broad, high-impact AI initiatives that have cross functional impact: Moving our AI usage from past narrow or siloed automation examples to execute a company operational transformation. - Partner with Product, Engineering, and operational leaders to embed AI capabilities into our customer-facing platform, internal business workflows, and core processes. - Serve as the ultimate technical authority for our data and AI infrastructure, making critical architectural decisions across MLOps pipelines, LLM orchestration frameworks, and distributed data systems. - Oversee the development of a scalable corporate data platform that serves as the foundational bedrock for all AI and machine learning capabilities. - Transform our internal knowledge base by building the systemic data architecture needed to turn unstructured information into intelligent, easily searchable, and actionable assets. - Re-build and evolve our company-wide data structures and connectivity pipelines to be optimized to deploy, run, and maintain AI models efficiently while lowering cost-to-serve. - Set the company wide tooling standards, maintain technical quality guardrails, and establish engineering best practices for embedded AI specialists working within distinct business units. - Actively support the implementation of key local solutions built by decentralized specialists, ensuring they have the tools and centralized platform support required to succeed. - Maintain high levels of ethical compliance by ensuring all global AI initiatives strictly adhere to data privacy, platform security, and ethical compliance standards. - Educate and empower teams across the organization to scale their own AI use productively, providing them with the structural frameworks needed to safely build and innovate within their functions. - Partner deeply with the People and Operations functions to champion organizational AI capability, replacing operational uncertainty with structured technical training loops that convert manual specialists into power-users of automated solutions. - Drive the organizational change management and literacy efforts required to reshape daily workflows, shifting company culture and habits from traditional manual processes to AI-assisted operations. CORE REQUIREMENTS - A genuine passion for artificial intelligence that goes far beyond product feature delivery. You possess a demonstrated interest in, and concrete evidence of driving, internal organizational change, specifically regarding how AI reshapes day-to-day employee workflows and habits. - Proven experience operating within a service-delivery model or a highly complex operational business, where data strategy directly impacts intricate, real-world workflows and diverse stakeholder ecosystems. - A history weighted heavily toward data engineering, distributed systems development, platform services infrastructure, or system architecture over front-end application product design. - A proven deep technical track record in distributed data systems, MLOps pipelines, and LLM orchestration. You can easily evaluate complex models and emerging technologies, serving as the ultimate technical authority for our infrastructure. - Documented success building, testing, and scaling complex asynchronous data structures, machine learning routing layers, or high-volume API integrations within modern software platforms. - The ability to view the organization holistically. You use your understanding of how interconnected technical platforms, business processes, and human teams interact, designing data and AI solutions that optimize entire workstreams rather than individual silos. - A proven track record of driving internal adoption for major technology or workflow shifts. You can break down complex AI frameworks for non-technical teams, guide employees through operational transitions, and successfully shift daily habits from manual work to AI-assisted processes. - Comprehensive familiarity with model validation systems, technical anomaly logging, data pipeline health metrics, and automated governance frameworks (e.g., custom logging models or open-source pipeline validation stacks). - BONUS : Background architecting semantic search solutions, internal retrieval-augmented generation engine layers, or multi-tenant customer data structures from zero-to-one phases. You'll also need - A reliable home internet connection and fluency in both written and spoken English HOW WE WORK TOGETHER AT OYSTER Our values guide the work we do, the decisions we make, and the culture that makes us special. We make it happen. We drive change. We build and give trust, and we are a united team. Our mission is to create a more equal world, one global hire at a time. Everything we do ladders up to our mission, and that doesn’t just mean building software. We develop programs, participate in workshops, and create dedicated teams to ensure we successfully support companies and knowledge workers in this new world of work. We embrace asynchronous communication and collaborative work and share our practices in the Oyster Public HQ https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d to help other global teams learn from our experiences. HOW YOU WORK With diverse locations, cultures, and needs, we created How YOU Work; https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395 a program supporting your whole human experience at Oyster: - Work from anywhere: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere. - Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country. - Mental health support: Access Plumm https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7, our mental well-being service. - Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet. Spend it on a wide range of options; see the benefits catalogue https://www.thanksben.com/employee-benefits-catalogue for ideas. - Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally. - WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly. ✨ THE BEST JOBS SHOULD BE AVAILABLE TO EVERYONE We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment. Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email jobs@oysterhr.com with the subject line: Interview Accommodations. Our available positions are on our careers page. Our team will only contact you from an @oysterhr.com email, and we will never ask for money as part of an interview process or job offer. If you receive a suspicious email about Oyster jobs or are directed to a site other than www.oysterhr.com/careers http://www.oysterhr.com/careers, please report it via our Compliance and Ethics Helpline https://faceup.com/c/8tpzyyye.", "summaryDescription" : "Senior Director, Data Platform and AI at Oyster. Skills: Data Platform, AI, Machine Learning, MLOps. Drive company-wide AI agenda. Scale AI initiatives into production systems", "createdAt" : "2026-06-13T21:56:14.554", "lastUpdated" : "2026-06-15T09:40:23.655", "ingestTimestamp" : "2026-06-13T21:56:14.554", "mongoId" : "6a2cb0be74d8ee00a09daeb1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data engineering", "Machine learning", "AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "MLOps pipelines", "LLM orchestration", "Distributed data systems", "Data architecture", "Data structures", "Connectivity pipelines", "AI initiatives", "Automation examples", "Data privacy", "Platform security", "Ethical compliance", "Organizational AI capability", "Technical training", "AI-assisted operations", "Leadership", "Data Platform", "Machine Learning", "MLOps", "System design", "Organizational transformation", "AI-native platform", "Knowledge management", "Automation layer frameworks", "ML orchestration frameworks", "Corporate data platform", "Unstructured information", "AI use productively", "Operational uncertainty", "Automated solutions", "Organizational change management", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 52, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a210ea374d8ee00a0af89ef", "title" : "Senior Data Scientist, Research, App Ecosystem and Trust", "industry" : "Technology", "salary" : { "min" : 150000.0, "max" : 250000.0, "currency" : "SGD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Data Scientist in Singapore, adjusted for the technology industry and senior experience level." }, "location" : "[Singapore, [Singapore], null, null, null, SG]", "locations" : [ "[Singapore, [Singapore], null, null, null, SG]" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T11:47:21.812", "fingerprint" : "53dfbbac8f3131e89c2a37268b2cae872bb01c64af7180ba133f8ac0b75855ed", "source" : "google", "language" : "en", "externalId" : "85133544715625158", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Singapore", "country" : "Singapore", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "1.2899175,103.8519072" } ], "locationText" : "Singapore, Singapore", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL, R, Spark, Scala, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, SageMaker, GCP, Vertex AI, Azure, ML Studio", "professionalSkills" : [ "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Statistical modeling", "Machine learning algorithms", "Data warehousing", "ETL processes", "Data visualization", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Machine learning algorithms", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "Data visualization", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, Data Science, Statistical Modeling, Data Engineering", "majorSkillsList" : [ "Machine Learning", "Data Science", "Statistical Modeling", "Data Engineering" ], "coreResponsibilities" : "Develop and deploy machine learning models, Design and implement data pipelines, Conduct advanced statistical analysis, Build and maintain BI dashboards, Collaborate with engineering teams, Research and apply new ML techniques, Ensure data quality and integrity, Communicate findings to stakeholders", "teamCollaboration" : "Cross-functional teams; 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Romania; Poland; Czech Republic", "employmentType" : "FULL_TIME", "professionalSkills" : [ "Case management", "Leave management", "Disability management", "Benefit administration" ], "hardSkillsList" : [ "Adjudicate leaves", "Review medical documentation", "Leverage duration guidelines", "Troubleshoot issues", "Remove barriers", "Solve problems", "Facilitate ramp-back plan", "Educate managers", "Educate business partners", "Communicate updates", "Ensure compliance", "Maintain system records", "Coordinate with HR", "Coordinate with Safety", "Coordinate with Legal", "Coordinate with Payroll", "Coordinate with Benefits" ], "softSkillsList" : [ "Critical thinking" ], "hardSkills" : [ { "name" : "Adjudicate leaves", "level" : "intermediate" }, { "name" : "Review medical documentation", "level" : "intermediate" }, { "name" : "Leverage duration guidelines", "level" : "intermediate" }, { "name" : "Troubleshoot issues", "level" : "intermediate" }, { "name" : "Remove barriers", "level" : "intermediate" }, { "name" : "Solve problems", "level" : "intermediate" }, { "name" : "Facilitate ramp-back plan", "level" : "intermediate" }, { "name" : "Educate managers", "level" : "intermediate" }, { "name" : "Educate business partners", "level" : "intermediate" }, { "name" : "Communicate updates", "level" : "intermediate" }, { "name" : "Ensure compliance", "level" : "intermediate" }, { "name" : "Maintain system records", "level" : "intermediate" }, { "name" : "Coordinate with HR", "level" : "intermediate" }, { "name" : "Coordinate with Safety", "level" : "intermediate" }, { "name" : "Coordinate with Legal", "level" : "intermediate" }, { "name" : "Coordinate with Payroll", "level" : "intermediate" }, { "name" : "Coordinate with Benefits", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Critical thinking" } ], "majorSkills" : "Case management, Disability and Leave, Employee relations", "majorSkillsList" : [ "Case management", "Disability and Leave", "Employee relations" ], "coreResponsibilities" : "Initiate inquiries about leave, Respond to inquiries about leave, Initiate inquiries about disability events, Respond to inquiries about disability events, Initiate inquiries about benefits, Respond to inquiries about benefits, Initiate inquiries about options, Respond to inquiries about options, Provide holistic case management services, Review medical documentation, Adjudicate leaves, Comply with leave plans, Comply with federal laws, Comply with state laws, Comply with benefit plans, Leverage duration guidelines, Use best practice tools, Use Amazon resources, Oversight of leave event, Critically assess case management plan, Adjust case management plan, Address sensitive situations, Respond to sensitive situations, Troubleshoot issues, Seek to remove barriers, Respond to employee impacting issues, Ensure right communication occurs, Identify problems, Solve problems, Facilitate smooth return to work, Facilitate ramp-back plan, Educate managers on employee concerns, Educate managers on employee needs, Educate business partners on employee concerns, Educate business partners on employee needs, Communicate regular updates to employees, Communicate regular updates to stakeholders, Ensure compliance with standard work, Ensure compliance with regulations, Ensure compliance with company policy, Maintain system records, Consult with third party administrator, Coordinate with third party administrator, Partner with third party administrator, Consult with HR, Coordinate with HR, Partner with HR, Consult with Safety, Coordinate with Safety, Partner with Safety, Consult with Legal, Coordinate with Legal, Partner with Legal, Consult with Payroll, Coordinate with Payroll, Partner with Payroll, Consult with Benefits, Coordinate with Benefits, Partner with Benefits, Consult with team members, Coordinate with team members, Partner with team members, Consult with other departments, Coordinate with other departments, Partner with other departments, Consult with systems, Coordinate with systems, Partner with systems, Perform other duties as assigned", "teamCollaboration" : "Cross functional environment; 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Solve problems; Critical thinking", "specialRequirements" : "Rotational shifts, Weekends, Weekdays", "qualificationsBasic" : "Bachelor's degree or equivalent experience, Customer service experience, Human Resource management experience, Case management experience, Leave & Disability management experience, Intermediate MS Word proficiency, Intermediate MS Excel proficiency, Intermediate MS Access proficiency, Intermediate MS Outlook proficiency, Intermediate MS PowerPoint proficiency, Very good written Italian (B2 CEFR), Very good verbal Italian (B2 CEFR), Very good written English (B2 CEFR), Very good verbal English (B2 CEFR)", "qualificationsPreferred" : "Critical thinking for problem solving, Relationship building, Influencing others, Cross functional environment experience, Time management, Ownership of deliverables, Demonstrated communication skills, Prior Leave experience, Prior Accommodation's experience, Case management systems experience, Reviewing cases for eligibility, Determining appropriate leave pay benefits, Determining appropriate disability pay benefits, Establishing case management plan, Executing case management plan, Guidance to employees on leave, Guidance to managers on leave, Guidance on disability plan, Guidance on accommodation, Guidance on human resources, Guidance on benefits, Guidance on employee matters, Working multiple projects independently, Working cases independently, Experience in changing priorities environment, Working with confidential information", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "*This role can be office based in Prague, Czech Republic. Additionally, this role can be performed remotely from any location within Romania, Poland, Slovakia and Czech Republic.* (!) Please submit your CV in English. At Amazon we believe that every day is still day one. We are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. If you’d like to help the Disability Leave Services (DLS) team build a best-in-class professional services program to deliver leave of absence, disability and accommodation services to Amazon employees, applicants, job seekers and candidates globally, this is your chance to make history by joining the amazing Disability & Leave Services Team. The DLS Case Manager provides case management for all types of leave of absence and disability life events. The DLS Case Manager is highly skilled in answering questions, understanding the employee’s situation, applying the appropriate benefits, responding to changing circumstances and needs, and paves the way for a connected and trusted case management experience. Case Managers are the single point of contact for an employee throughout an entire leave of absence or disability event. This is an individual contribution (IC) role with no direct reports. Key job responsibilities • Initiate and respond to inquiries about leave and disability events, benefits, and options available to employees • Serve as a point of contact for assigned employees to provide holistic case management services, including reviewing medical documentation to adjudicate leaves in compliance with the corresponding leave plans, federal and state laws and benefit plans as defined by Amazon • Leverage duration guidelines, best practice tools and Amazon resources to support oversight of a leave event as appropriate • Critically assess and adjust the case management plan to an employee’s changing needs • Address and respond to sensitive situations • Troubleshoot issues and seek to remove barriers before, during, or after a leave event • Respond to employee impacting issues that may arise during the leave event and ensure the right communication occurs • Identify and solve problems that may arise, sometimes with limited information • Facilitate a smooth return to work and ramp-back plan for employees returning to the workplace • Educate managers and business partners on employee concerns and needs prior to being off or returning back to work • Communicate regular updates to employees and stakeholders both verbally and in writing • Ensure compliance with standard work, federal/state regulations, and company policy • Maintain system records to ensure accurate and timely information/documentation • Consult, coordinate and partner with our third party administrator, HR, Safety, Legal, Payroll, Benefits, team members and other departments/systems as appropriate • Other duties as assigned • Being able to work on rotational shifts in both weekends and weekdays Basic Qualifications: - Bachelor’s degree from accredited university or equivalent experience - Experience in customer service or Human Resource management or Case management or Leave & Disability management role - Intermediate proficiency in MS Word, Excel, Access, Outlook and PowerPoint - Very good proficiency in written and verbal in Italian (B2 CEFR) and English (B2 CEFR). Preferred Qualifications: - Ability to apply critical thinking and identify issues for problem solving - Ability to build strong relationships and influence others while working in a cross functional environment - Strong time management and ownership of deliverables Strong & demonstrated communication skills - verbal as well as written Prior Leave and/or Accommodation’s experience, to include: previous work in a leave of absence and/or disability claim management role, with experience using case management systems, reviewing cases for eligibility, determining the appropriate leave and/or disability pay benefits that apply to a specific situation, and establishing/executing a case management plan. - Experience providing guidance to employees or managers on leave of absence, disability plan, accommodation, human resources, benefits, or employee matters - Experience working multiple projects or cases independently in environment with changing priorities - Experience working with confidential information. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. 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" : "Case Manager with Italian and English at Amazon Czech Republic Services s.r.o.. Skills: Case management, Disability and Leave, Employee relations. Initiate inquiries about leave. 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Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve. Our Commitment As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day. Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees. United States-Georgia-Atlanta", "summaryDescription" : "GA/AL/MS Pump Station and Pipelines Business Class Leader. Works cooperatively with other area business class leaders. 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Skills: Data center operations, Hardware support. Install and configure servers. 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"salary" : { "min" : 2500000.0, "max" : 4500000.0, "currency" : "MXN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Director level in Mexico City's media industry, adjusted for YouTube's company size and the specific role's scope." }, "location" : "[Mexico City, CDMX, Mexico, [Mexico City, CDMX, Mexico], Mexico City, null, CDMX, MX]", "locations" : [ "[Mexico City, CDMX, Mexico, [Mexico City, CDMX, Mexico], Mexico City, null, CDMX, MX]" ], "timestamp" : "2026-06-16T15:11:38.591", "fingerprint" : "70135a33214acb21c3c57c3f4fa8fe607dc4f811274548f67fa4323b9154a97c", "source" : "google", "language" : "en", "externalId" : "130065512586453702", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Mexico City", "state" : "CDMX", "country" : "Mexico", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "19.4326296,-99.1331785" } ], "locationText" : "Mexico City, CDMX, Mexico", "summaryDescription" : "Head of Brand, 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"SEK", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Junior Mechanical Technician in Vasteras, Sweden, adjusted for the technology industry and company size." }, "location" : "Vasteras, Vastmanland County, SWE", "locations" : [ "Vasteras, Vastmanland County, SWE" ], "timestamp" : "2026-06-15T02:24:18.638", "fingerprint" : "9726ecf1ef63add8da82b35a1052909b434b5d8022a479d21f726ceb8b7bb672", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10436718/apply", "externalId" : "d9574ef5-48de-4c40-84f3-2217eb3a0396", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vasteras", "state" : "Vastmanland County", "country" : "Sweden", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "59.6110992,16.5463679" } ], "locationText" : "Vasteras, Vastmanland County, Sweden", "employmentType" : "FULL_TIME", "technicalSkills" : "Mechanical equipment, Electrical equipment, Controls equipment", "professionalSkills" : [ "Operations management", "Maintenance planning", "Root cause analysis", "Risk assessment", "Method statements" ], "hardSkillsList" : [ "Filter changes", "Tank inspections", "Legionella testing", "Pump maintenance" ], "softSkillsList" : [ "Mentoring", "Guidance" ], "hardSkills" : [ { "name" : "Filter changes", "level" : "intermediate" }, { "name" : "Tank inspections", "level" : "intermediate" }, { "name" : "Legionella testing", "level" : "intermediate" }, { "name" : "Pump maintenance", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" }, { "name" : "Guidance" } ], "majorSkills" : "Mechanical equipment maintenance, Cooling systems operation, Troubleshooting", "majorSkillsList" : [ "Mechanical equipment maintenance", "Cooling systems operation", "Troubleshooting" ], "coreResponsibilities" : "Ensure operation of cooling equipment, Maintain mechanical equipment, Maintain electrical equipment, Maintain controls equipment, Maintain high reliability, Maintain performance, Reduce operating costs, Troubleshoot cooling equipment, Plan preventative maintenance, Coordinate preventative maintenance, Conduct preventative maintenance, Identify root causes of faults, Plan corrective maintenance, Deliver corrective maintenance, Purchase spares, Purchase parts, Store spares, Store parts, Mentor technicians, Guide technicians, Supervise contractors, Perform filter changes, Perform tank inspections, Perform legionella testing, Perform pump maintenance, Perform first level troubleshooting, Develop risk assessments, Implement risk assessments, Develop method statements, Implement method statements, Take daily operational readings, Provide readings for reporting, Input EAM data, Manage EAM data, Update maintenance reports, Update maintenance planners, Perform basic support concepts, Prioritize tasks", "teamCollaboration" : "Cross-functional teams; Work with AWS teams", "domainKnowledge" : "Data center operations; Cooling systems; Mechanical infrastructure; Electrical infrastructure; Controls infrastructure", "domainList" : [ "data-center-operations", "cooling-systems", "mechanical-infrastructure", "electrical-infrastructure", "controls-infrastructure" ], "domainSpecificKnowledge" : [ "Data center operations", "Cooling systems", "Mechanical infrastructure", "Electrical infrastructure", "Controls infrastructure" ], "toolProficiency" : [ "EAM" ], "documentationSkills" : "Maintenance reports; Maintenance planners", "innovationCreativity" : "Drive innovation", "problemSolvingSkills" : "Troubleshooting; Root cause analysis", "specialRequirements" : "Work on call, Work out of hours, Travel between sites", "outcomesObjectives" : "Maintain better than 99.999% uptime; Keep operating costs at minimum", "qualificationsBasic" : "2+ years mechanical equipment experience, Ability to travel between sites, EU Drivers license", "qualificationsPreferred" : "Cooling systems experience, Troubleshooting cooling equipment, Training in cooling systems", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Data Center Engineer (Mechanical Equipment) will be responsible for ensuring the overall operation and maintenance of all cooling and associated mechanical / electrical / controls equipment within the nominated Datacenters. This equipment supports mission-critical servers and must maintain better than 99.999% uptime. The Data Center Engineering Technician (Mechanical Equipment) will continue to maintain high reliability and performance while keeping operating costs in facilities at a minimum, the engineer will drive innovation to reduce operational costs. The Data Center Engineer (Mechanical Equipment) are Amazon’s front line when it comes to hands-on electrical and mechanical equipment troubleshooting for cooling equipment including Air Handling Units, Computer Room Air Handling Units and ancillary equipment initially, with scope to increase in the future to other mechanical infrastructure. They will plan, coordinate, manage and conduct preventative maintenance on assigned equipment. They will also identify root causes of faults, plan and deliver reactive and corrective maintenance. AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Key job responsibilities • Plan out, prepare sequence of operations and deliver preventative maintenance across all nominated Data Center sites. • Identify, purchase and store spares and parts required for planned and reactive works. • Conduct root cause analysis on failures and action remediation. • Mentor and guide on site Engineering Operations Technicians unfamiliar with the equipment for immediate on site reaction during an event. • Supervise contractors who perform servicing or preventive maintenance. • Perform maintenance tasks to include: filter changes, tank inspections, legionella testing, pump maintenance. • Perform first level trouble-shooting. • Develop and implement risk assessments and method statements for works. • Work on call or out of hours when required, though standard working arrangement will be Monday to Friday normal office hours. • Take daily operational readings and provide to Senior Engineers for metrics reporting. • Input and management of EAM for assigned assets. • Update maintenance reports and planners. • Perform basic support concepts such as ticketing systems, root cause analysis, and task prioritization. Travel Between Data Center sites is involved About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Basic Qualifications: - 2+ years of relevant work experience within the mechanical equipment field. (Pumps, engines, cooling systems etc) - Ability to travel between all nominated sites on a daily or weekly basis. - EU Drivers license. Preferred Qualifications: - Particular experience in cooling systems (AHUs, CRAHUs, HVAC systems, Generators, Pumps, industrial water systems) is advantageous. - Demonstrated capability in understanding and troubleshooting of cooling equipment and fundamentals. - Training or certification in cooling systems a strong benefit. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. 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" : "Mechanical Technician, Data Center Engineering and Operations, Data Center Engineering and Operations at Amazon Data Services Sweden AB. Skills: Mechanical equipment maintenance, Cooling systems operation, Troubleshooting. Ensure operation of cooling equipment. Maintain mechanical equipment", "postedDate" : "2026-06-13T04:27:00.739", "createdAt" : "2026-06-13T04:27:00.739", "lastUpdated" : "2026-06-15T02:24:18.638", "ingestTimestamp" : "2026-06-13T04:27:00.739", "mongoId" : "6a2176f474d8ee00a0c1b5d5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10436718/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Filter changes", "Tank inspections", "Legionella testing", "Pump maintenance", "Mentoring", "Guidance", "Mechanical equipment maintenance", "Cooling systems operation", "Troubleshooting", "Operations management", "Maintenance planning", "Root cause analysis", "Risk assessment", "Method statements", "Data center operations", "Cooling systems", "Mechanical infrastructure", "Electrical infrastructure", "Controls infrastructure", "EAM" ], "skillCount" : 20, "jobCategory" : "engineering", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a21770d74d8ee00a0c1ba5d", "title" : "AI Data Associate with French", "company" : "Nuqtat Al Taknalojia", "industry" : "Editorial, Writing, Content Management, Machine Learning Data Operatio, Artificial Intelligence", "salary" : { "min" : 14000.0, "max" : 20000.0, "currency" : "JOD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level AI Data Associate in Amman, Jordan, adjusted for the technology industry." }, "location" : "Amman, JOR", "locations" : [ "Amman, JOR" ], "timestamp" : "2026-06-15T05:33:26.150", "fingerprint" : "6ca041e132ba7d04ac842d9f34a10f05574d86118c99d9ee82005e7a7542397d", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10435530/apply", "externalId" : "e7711eb5-1fb9-47a5-8ace-54bb3776aba2", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Amman", "country" : "Jordan", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "31.9515694,35.9239625" } ], "locationText" : "Amman, Jordan", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "AI, Generative AI, Large language models", "hardSkillsList" : [ "Data labeling", "Dialogue evaluation" ], "hardSkills" : [ { "name" : "Data labeling", "level" : "intermediate" }, { "name" : "Dialogue evaluation", "level" : "intermediate" } ], "majorSkills" : "Data labeling, AI", "majorSkillsList" : [ "Data labeling", "AI" ], "coreResponsibilities" : "Maintain strict confidentiality, Work with diverse data types, Deliver high-quality labelled data, Meet KPIs, Generate human insight data, Make sound judgments, Make logical decisions, Pivot between requirements, Support daily operational deliverables, Analyze root causes, Identify error patterns, Propose solutions, Enhance labeling quality, Identify process issues, Suggest changes to unblock operations, Provide floor support, Clarify internal queries", "domainKnowledge" : "Generative AI; Large language models", "domainList" : [ "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Generative AI", "Large language models" ], "toolProficiency" : [ "In-house tools" ], "communicationSkills" : "Business writing; Professional correspondence", "problemSolvingSkills" : "Structured problem-solving; Root cause analysis", "outcomesObjectives" : "Meet KPIs", "qualificationsBasic" : "Associate's Degree or related work experience, B1+ English fluency, C1+ French fluency, Business writing skills, Advanced reading comprehension, Analytical thinking, Structured problem-solving, Interpret detailed instructions, Proficient research skills, Proven attention to detail", "qualificationsPreferred" : "Bachelor's degree, 2+ years professional experience, Leverage open-source resources, Adapt to fast-paced environments, 2-3 years project coordination, Manage stakeholder relationships, Advanced Microsoft Office Suite proficiency", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. Amazon is investing in generative AI and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for those candidates who just don’t think out of the box, but make the box they are in ‘Bigger’. The future is now, do you want to be a part of it? Then read on! Key job responsibilities - Maintain and follow strict confidentiality as customer privacy is our most important tenet - Work with a range of different types of data including, but not limited to: text, speech, audio, image, and video - Deliver high-quality labelled data, using guidelines provided to meet our KPIs and using in-house tools and software, as part of Amazon's commitment to developing and deploying AI responsibly. - Demonstrate proficiency in generating high quality human insight data across a range of modalities, inclusive of text, image video and audio. - Capable of making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks. - Eye for detail and ability to pivot from one category of requirement to another instantaneously. - Demonstrate support on daily operational deliverables for multiple task types assigned to you and the team - Analyze root causes, identify error patterns, and propose solutions to enhance the quality of labeling tasks and their outputs. - Responsible for identifying day-to-day process and operational issues in Standard Operating Procedure, tools and suggest changes to unblock operations - Demonstrate ownership in floor support to clarify internal queries during execution on need basis. A day in the life We are looking for an AI Data Associate to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data. Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial. Basic Qualifications: - - An Associate’s Degree or related work experience - - Good working knowledge (B1+) in both spoken and written English - - C1+ or equivalent fluency in French language - - Strong business writing skills with ability to create reports, proposals, and professional correspondence - - Advanced reading comprehension with ability to analyze complex business documents - - Developed analytical thinking and structured problem-solving capabilities - - Strong ability to interpret and implement detailed instructions across various projects - - Proficient research skills with experience gathering and synthesizing information from multiple sources - - Proven attention to detail in managing complex tasks and documents Preferred Qualifications: - Bachelor’s degree in a relevant field - 2+ years of professional work experience with demonstrated task execution ability - Proven capacity to leverage open-source resources effectively for comprehensive research purposes - Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy - 2-3 years project coordination or management experience - Experience managing stakeholder relationships across departments - Advanced proficiency in Microsoft Office Suite and common business applications. Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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" : "AI Data Associate with French at Nuqtat Al Taknalojia. Skills: Data labeling, AI. Maintain strict confidentiality. Work with diverse data types", "postedDate" : "2026-06-13T18:15:09.277", "createdAt" : "2026-06-13T18:15:09.277", "lastUpdated" : "2026-06-15T05:33:26.150", "ingestTimestamp" : "2026-06-13T18:15:09.277", "mongoId" : "6a21770d74d8ee00a0c1ba5d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10435530/apply", "salaryBand" : "<30k", "hasSalary" : false, "allSkills" : [ "Data labeling", "Dialogue evaluation", "AI", "Generative AI", "Large language models", "In-house tools" ], "skillCount" : 6, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3051cbf292fd229cf06d4c", "title" : "Merchant Security Expert with Spanish and English", "company" : "SumUp", "industry" : "FinTech", "salary" : { "min" : 65000.0, "max" : 95000.0, "currency" : "BGN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for FinTech in Sofia, Bulgaria, adjusted for mid-seniority and full-time employment." }, "location" : "Sofia, Bulgaria", "locations" : [ "Sofia", "Bulgaria" ], "timestamp" : "2026-06-16T09:36:44.092", "fingerprint" : "189df21854cfafe74ec3852e1dd4ca1a1508a18e931bb27d855692813d995637", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://sumup.com/careers/positions/8416344002?gh_jid=8416344002", "externalId" : "8416344002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Sofia", "country" : "Bulgaria", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "42.6977028,23.3217359" } ], "locationText" : "Sofia, Bulgaria", "professionalSkills" : [ "Decision making" ], "majorSkills" : "Merchant security, Risk and fraud", "majorSkillsList" : [ "Merchant security", "Risk and fraud" ], "coreResponsibilities" : "Address transaction-related requests, Adhere to security rules, Contact merchants, Verify documents, Monitor merchant behavior, Adjust payment limits, Provide support to customers", "teamCollaboration" : "Customer Support team; Risk and Fraud Team", "domainKnowledge" : "AML rules; Internal T&Cs rules", "domainList" : [ "aml-rules", "internal-t-cs-rules" ], "domainSpecificKnowledge" : [ "AML rules", "Internal T&Cs rules" ], "continuousLearning" : "Individual learning budget; Educational leave", "qualificationsBasic" : "Excellent Spanish and English skills, Communication skills, Patience, Curiosity, Persistence, Organizational skills, Attention to detail", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "At SumUp, we are driven to empower small businesses across the globe by de-hassling their lives and helping them to succeed. Our vision as a global FinTech company is to build the first-ever global card acceptance brand, and we are well on our way as small businesses in over 31 countries around the world rely on SumUp to get paid.If you would like to be part of a global team, putting business partnering and innovation in the core of its priorities, this might be the right role for you. Join our dynamic and international Customer Support team, specializing in Risk & Fraud. Our team spans across four continents, bringing together diverse talents from over 60 countries. We thrive on challenges and collaborate seamlessly to ensure the success of small businesses globally. What you’ll be doing: Proactively addressing a variety of transaction-related requests from our merchants while adhering to security rules and procedures. Acting as the voice of our internal Risk and Fraud Team by contacting merchants and verifying documents based on risk assessments. Monitoring merchant behavior in compliance with AML and internal T&Cs rules. Utilizing decision-making abilities for reviewing customer business and adjusting payment limits. Providing support to Dutch and English-speaking customers through various communication channels, via phone, chat or email. The role primarily involves specialized security calls with low phone volume, and each issue is handled through the most suitable channel. You’ll be great for this role if: You possess excellent language skills in both Spanish and English Communication is your strength, and you handle customer interactions with ease and patience. Curiosity and persistence drive you to solve issues efficiently. Your organizational skills shine, even in stressful situations Attention to detail is a defining characteristic Why you should join SumUp: \uD83C\uDF0D You’ll play a key role in a scale-up that in turn is part of a truly global team of 3000+ people from 60+ countries, spread across 4 continents. \uD83D\uDE80 You'll have the opportunity to make an impact irrespective of your job description. You'll have the space to drive your career and take ownership of projects. \uD83D\uDCAF You'll get a Referral bonus if your friend is hired successfully. \uD83C\uDF34 You’ll receive 25 days’ paid leave, increasing with tenure, and paid vacation for certain occasions. \uD83D\uDD0B You’d enjoy a paid 1 month Sabbatical vacation after 3 years. \uD83D\uDCDA You’ll receive an individual learning budget and can take 10 days educational leave to expand your skillset. \uD83C\uDF4E You’d have monthly digital food vouchers. ⭐️ You’d have monthly budget for a wide choice of benefits and discounts ranging from transport, food, learning and more (re:benefit platform) \uD83D\uDE8C\uD83C\uDF57\uD83D\uDCA1\uD83C\uDF81. ❤️ You'd have access to additional health insurance, life insurance and co-sponsored Multisport card \uD83C\uDFBE. \uD83D\uDC9C You’d enjoy funded therapy & coaching sessions with licensed psychotherapists. \uD83D\uDC76\uD83C\uDFFC You’d enjoy a child birth/adoption bonus. \uD83D\uDE8C You’d have access to a free shuttle buses from Joliot-Curie metro station and more. This job is on-site - Sofia MORE ABOUT US: We believe in the everyday hero.Small business owners are at the heart of all we do, so we create powerful, easy-to-use financial solutions to help them run their businesses. With a founder’s mentality and a 'team-first’ attitude, our diverse teams across Europe, South America and the United States work together to ensure that the small business owners we partner with can be successful doing what they love. SumUp is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. SumUp does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age or any other basis protected by applicable laws or prohibited by company policy. SumUp also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.SumUp will not accept unsolicited resumes from any source other than directly from a candidate. #SumUpOps Job Application Tip We recognise that candidates feel they need to meet 100% of the job criteria in order to apply for a job. Please note that this is only a guide. If you don’t tick every box, it’s ok too because it means you have room to learn and develop your career at SumUp.", "summaryDescription" : "Merchant Security Expert with Spanish and English at SumUp. Skills: Merchant security, Risk and fraud. Address transaction-related requests. Adhere to security rules", "postedDate" : "2026-06-15T23:20:21.794", "createdAt" : "2026-06-15T23:20:21.794", "lastUpdated" : "2026-06-16T09:36:44.092", "ingestTimestamp" : "2026-06-15T23:20:21.794", "mongoId" : "6a3051cbf292fd229cf06d4c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Merchant security", "Risk and fraud", "Decision making", "AML rules", "Internal T&Cs rules" ], "skillCount" : 5, "jobCategory" : "sales", "jobSubcategory" : "customer_success", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c92ed74d8ee00a0986e16", "title" : "Data Analyst with AI skills", "company" : "Xebia", "industry" : "Consulting", "salary" : { "min" : 120000.0, "max" : 180000.0, "currency" : "PLN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Mid-level Data Analyst with AI skills in the Technology industry in Poland, adjusted for seniority and company size." }, "location" : "Poland", "locations" : [ "Poland" ], "timestamp" : "2026-06-15T07:48:47.231", "fingerprint" : "0f36e4ca63cac5c29d11a406b789aac2663931e086e62ca839a94649afcb6e98", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/xebiacee/jobs/6018324004", "externalId" : "6018324004", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Poland", "continent" : "eu", "workMode" : "onsite" } ], "locationText" : "Poland", "technicalSkills" : "Python, Jupyter Notebooks, Pandas, NumPy, DuckDB, SQL, APIs, AWS, Azure, GCP, Databricks, Snowflake, Docker, Kubernetes", "professionalSkills" : [ "Data engineering", "Business intelligence", "Analytics engineering", "Quantitative analysis", "ETL development", "Data modelling", "Data warehousing", "Data governance", "Data security", "Performance optimization" ], "hardSkillsList" : [ "Data pipeline development", "Data transformation", "Data validation", "Data documentation", "Data ingestion", "SQL optimization", "Dashboard design", "KPI prioritization", "BI dashboard creation", "Data analysis" ], "softSkillsList" : [ "Independent" ], "hardSkills" : [ { "name" : "Data pipeline development", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data validation", "level" : "intermediate" }, { "name" : "Data documentation", "level" : "intermediate" }, { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "SQL optimization", "level" : "intermediate" }, { "name" : "Dashboard design", "level" : "intermediate" }, { "name" : "KPI prioritization", "level" : "intermediate" }, { "name" : "BI dashboard creation", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Independent" } ], "majorSkills" : "Data pipelines, Business Intelligence, Data products, Cloud infrastructure", "majorSkillsList" : [ "Data pipelines", "Business Intelligence", "Data products", "Cloud infrastructure" ], "coreResponsibilities" : "Lead development of scalable ETL/analytics pipelines, Lead development of customer-facing analytics, Work with stakeholders to clarify questions, Map metrics to available data, Prioritize feasible KPIs, Build reliable pipelines, Ingest data, Validate data, Transform data, Document data, Design BI dashboards, Generate insightful dashboards, Enable customers to filter data, Enable customers to analyze data, Ensure solutions scale across customers, Leverage cloud infrastructure, Optimize performance", "teamCollaboration" : "Work with stakeholders; Cross-functional teams", "domainKnowledge" : "AI tooling; Cloud data stacks; ML frameworks; BI platforms; Operational data; Multi-tenant setups; Columnar/Parquet outputs; Analysis-ready datasets; Curated datasets; ERP systems", "domainList" : [ "ai-tooling", "cloud-data-stacks", "ml-frameworks", "bi-platforms", "operational-data", "multi-tenant-setups", "columnar-parquet-outputs", "analysis-ready-datasets", "curated-datasets", "erp-systems" ], "domainSpecificKnowledge" : [ "AI tooling", "Cloud data stacks", "ML frameworks", "BI platforms", "Operational data", "Multi-tenant setups", "Columnar/Parquet outputs", "Analysis-ready datasets", "Curated datasets", "ERP systems" ], "toolProficiency" : [ "Jupyter Notebooks", "Pandas", "NumPy", "DuckDB", "Apache Superset", "Docker", "Kubernetes" ], "documentationSkills" : "Data documentation", "problemSolvingSkills" : "Root cause analysis", "specialRequirements" : "Work from EU region, Work permit required", "outcomesObjectives" : "Turn data into insights; Turn data into workflows; Turn data into data products; Provide visual insights into KPIs", "qualificationsBasic" : "Proven experience developing data pipelines, Hands-on use of Pandas, Hands-on use of NumPy, Hands-on use of DuckDB, Familiarity with cloud environments, Expertise in SQL, Experience using BI tools, Expertise in dashboard design", "qualificationsPreferred" : "Experience with Apache Superset, Hands-on experience with cloud environments, Hands-on experience with containerization technologies, Knowledge of rights management in BI tools, Familiarity with parallelizing ETL processes, Familiarity with workflow orchestration", "remoteFriendly" : true, "rawDescription" : "Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. About the project: We are building a modern analytics and Business Intelligence solution that integrates operational data from multiple ERP systems across countries, and turns it into reliable, customer-facing insights, analytical workflows, and reusable data products. You will be: leading the development of scalable ETL/analytics pipelines and customer-facing analytics - from requirements through published datasets and usable dashboards - for multi-tenant customer setups, working with stakeholders to clarify questions and metrics, map them to available ERP/operational data, and prioritize KPIs that are feasible, testable, and maintainable, building reliable pipelines that ingest, validate, transform, and document data into curated, analysis-ready datasets (e. g. columnar/Parquet outputs, consistent schemas), suitable for SQL-based reporting and dashboards, designing and implementing BI dashboards that use curated data to provide visual insights into relevant KPIs, enabling customers to filter, analyze, and interpret data with ease, ensuring solutions can scale across multiple customers with minimal effort, leveraging cloud infrastructure and optimizing performance where necessary. Your profile: strong ability to work independently and proactively in a fast-paced project, knowledgable in advanced AI tooling for productivity, including MCP, agent skills, harness engineering (Claude code/Cursor/Codex), Worktrees, proven experience developing data pipelines using Python and Jupyter Notebooks, hands-on use of Pandas, NumPy, and DuckDB (or equivalent analytical SQL engines) for transforms, validation, and performance-conscious processing, familiarity with cloud environments and utilizing SDKs to extract data from various sources, including Azure, AWS, APIs, and SQL databases, expertise in SQL for data manipulation and creating normalized datasets from multiple systems, experience using BI tools to create and manage datasets and generate insightful dashboards, expertise in dashboard design, including the use of filters and other interactive elements for deep data analysis, experience with Apache Superset is a strong plus. Work from the European Union region and a work permit are required. Nice to have: hands-on experience with cloud environments and containerization technologies (e.g., Docker, Kubernetes), knowledge of rights management in BI tools for data security and access control, familiarity with parallelizing ETL processes and workflow orchestration to improve efficiency and scalability. Recruitment Process: CV review – HR call – Interview – Client Interview – Decision", "summaryDescription" : "Data Analyst with AI skills at Xebia. Skills: Data pipelines, Business Intelligence, Data products, Cloud infrastructure. Lead development of scalable ETL/analytics pipelines. Lead development of customer-facing analytics", "postedDate" : "2026-06-13T21:27:17.668", "createdAt" : "2026-06-13T21:27:17.668", "lastUpdated" : "2026-06-15T07:48:47.231", "ingestTimestamp" : "2026-06-13T21:27:17.668", "mongoId" : "6a2c92ed74d8ee00a0986e16", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data pipeline development", "Data transformation", "Data validation", "Data documentation", "Data ingestion", "SQL optimization", "Dashboard design", "KPI prioritization", "BI dashboard creation", "Data analysis", "Independent", "Data pipelines", "Business Intelligence", "Data products", "Cloud infrastructure", "Data engineering", "Business intelligence", "Analytics engineering", "Quantitative analysis", "ETL development", "Data modelling", "Data warehousing", "Data governance", "Data security", "Performance optimization", "AI tooling", "Cloud data stacks", "ML frameworks", "BI platforms", "Operational data", "Multi-tenant setups", "Columnar/Parquet outputs", "Analysis-ready datasets", "Curated datasets", "ERP systems", "Jupyter Notebooks", "Pandas", "NumPy", "DuckDB", "Apache Superset", "Docker", "Kubernetes" ], "skillCount" : 42, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c601274d8ee00a08f1114", "title" : "Coding, Data and Automations Experts", "company" : "Vetto", "salary" : { "min" : 45.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "São Paulo, São Paulo, Brazil", "locations" : [ "São Paulo", "São Paulo", "Brazil" ], "timestamp" : "2026-06-14T19:09:31.403", "fingerprint" : "6166d023d47e76011faa2c8f7c48d5b99737b59dc53b36f82563e2b861aa89df", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/vetto/jobs/4183744009", "externalId" : "4183744009", "structuredLocations" : [ { "city" : "São Paulo", "state" : "São Paulo", "country" : "Brazil", "continent" : "sa", "source" : "llm", "workMode" : "onsite", "geo" : "-23.5506507,-46.6333824" } ], "locationText" : "São Paulo, São Paulo, Brazil", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, JavaScript, SQL", "professionalSkills" : [ "Technical judgment" ], "hardSkillsList" : [ "Coding", "Data analysis", "Automation" ], "hardSkills" : [ { "name" : "Coding", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Automation", "level" : "intermediate" } ], "majorSkills" : "AI, Coding, Data, Automation", "majorSkillsList" : [ "AI", "Coding", "Data", "Automation" ], "coreResponsibilities" : "Review technical scenarios, Improve technical scenarios, Upgrade weak scenarios", "domainKnowledge" : "Artificial Intelligence", "domainList" : [ "artificial-intelligence" ], "domainSpecificKnowledge" : [ "Artificial Intelligence" ], "toolProficiency" : [ "n8n", "Make", "Zapier" ], "problemSolvingSkills" : "Identify decision trade-offs", "specialRequirements" : "AI is not allowed", "outcomesObjectives" : "Test technical judgment", "qualificationsBasic" : "Writes and runs code professionally", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## \uD83C\uDFE2 About Vetto Vetto is a global platform that connects top-tier professionals to strategic Artificial Intelligence projects around the world. Our mission is to build trust, quality, and long-term value within the AI ecosystem, for both exceptional talent and companies operating at the forefront of technology. ## \uD83D\uDCD6 About the project We're recruiting coding, data, and automation experts to review and improve real-world technical scenarios used to train AI assistants. Your job isn't to write tutorials. It's to think like a senior engineer: identify logical flaws, edge cases, bad practices, and decision trade-offs — then upgrade weak scenarios so they truly test technical judgment. ## \uD83D\uDC64 Who can apply • Software Engineers / Developers (any stack) • Data Analysts & Data Engineers • Automation & Workflow Specialists (n8n, Make, Zapier, etc.) • Anyone who writes and runs code professionally — Python, JavaScript, SQL, or any language ## \uD83E\uDDE9 Selection In this application, you will answer questions following the instructions below. If selected, you will be invited to review real case scenarios as part of the project. ## \uD83D\uDCB0 Compensation Payment will be US$ 30 per approved task, converted and paid in your local currency. Each task takes approximately 40 minutes, which corresponds to an effective rate of about US$ 45 per hour. ## \uD83E\uDD11 Refer People -> Earn Money If you’d like to refer someone, you can earn $20 USD for each approved referral. To participate, go to the Opportunities page on the platform (https://work.vetto.ai/opportunities) and click “Refer & Earn” to share your personal referral link. ‼️ AI is not allowed. If we spot AI use, we’ll block the application. ⚠️ This application form must be completed entirely in English.", "summaryDescription" : "Coding, Data and Automations Experts at Vetto. Skills: AI, Coding, Data, Automation. Review technical scenarios. Improve technical scenarios", "postedDate" : "2026-06-12T22:24:28.282", "createdAt" : "2026-06-12T22:24:28.282", "lastUpdated" : "2026-06-14T19:09:31.403", "ingestTimestamp" : "2026-06-12T22:24:28.282", "mongoId" : "6a2c601274d8ee00a08f1114", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 93600, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Coding", "Data analysis", "Automation", "AI", "Data", "Technical judgment", "Artificial Intelligence", "n8n", "Make", "Zapier" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "engineering", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "68b706987fc9a711f0f6fc8a", "title" : "Senior Data Scientist, Data and Machine Learning, WWPS US Federal", "company" : "Amazon Web Services, Inc.", "industry" : "Project/Program/Product Management--Technical, Science, Cloud Computing", "salary" : { "min" : 143300.0, "max" : 247600.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Jessup, Maryland, USA", "locations" : [ "Jessup, Maryland, USA" ], "timestamp" : "2026-06-15T03:19:09.164", "fingerprint" : "5f39765562fff076a8bc71e22c07af7f5edcebef2fe2cc9c8a53a3e1039a1cbc", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3054883/apply", "externalId" : "b0e2cf35-8b6c-440c-b87a-04875d5d62c8", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Jessup", "state" : "Maryland", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "39.1470015,-76.7699177" } ], "locationText" : "Jessup, Maryland, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, Machine Learning, Generative AI, LLMs, AWS, Python, R, Scala, Spark, SQL, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, Regression, Classification, Clustering, Time-series, A/B testing, Causal inference, AWS S3, AWS Glue, AWS SageMaker, AWS Athena, GCP BigQuery, GCP Vertex AI, Azure Synapse, Azure ML Studio", "professionalSkills" : [ "Business acumen", "Customer requirements", "Solution design", "Data transformation", "Mission transformation" ], "hardSkillsList" : [ "Data science", "Machine learning", "Generative AI", "Algorithm development", "MLOps pipeline construction", "Statistical analysis", "Data mining", "Deep learning", "Numerical optimization", "Data structures", "SIGINT production chains" ], "hardSkills" : [ { "name" : "Data science", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Generative AI", "level" : "intermediate" }, { "name" : "Algorithm development", "level" : "intermediate" }, { "name" : "MLOps pipeline construction", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Data mining", "level" : "intermediate" }, { "name" : "Deep learning", "level" : "intermediate" }, { "name" : "Numerical optimization", "level" : "intermediate" }, { "name" : "Data structures", "level" : "intermediate" }, { "name" : "SIGINT production chains", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, Generative AI, Data Science, MLOps", "majorSkillsList" : [ "Machine Learning", "Generative AI", "Data Science", "MLOps" ], "coreResponsibilities" : "Research AI algorithms, Design AI algorithms, Develop AI algorithms, Evaluate AI algorithms, Design MLOps pipelines, Construct MLOps architectures, Interact with customers, Understand business problems, Aid customers in AI solution implementation, Deliver briefing sessions, Deliver deep dive sessions, Guide customers on adoption patterns, Guide customers on paths to production, Create best practice recommendations, Deliver best practice recommendations, Create tutorials, Deliver tutorials, Create sample code, Deliver sample code, Create presentations, Deliver presentations, Provide customer feedback, Provide market feedback", "teamCollaboration" : "AI/ML Scientists; Architects; Product teams; Engineering teams; Customers", "domainKnowledge" : "Signals Intelligence; Cyber Operations; Intelligence Community; Cloud computing; Generative AI; Large Language Models", "domainList" : [ "signals-intelligence", "cyber-operations", "intelligence-community", "cloud-computing", "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Signals Intelligence", "Cyber Operations", "Intelligence Community", "Cloud computing", "Generative AI", "Large Language Models" ], "toolProficiency" : [ "AWS", "SageMaker", "Python", "R", "SQL", "Dbt", "Snowflake", "BigQuery", "Redshift", "Databricks", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow" ], "communicationSkills" : "Executive presentations; Technical writing; Customer briefings; Deep dive sessions", "innovationCreativity" : "Drive feature innovation", "problemSolvingSkills" : "Data challenges; Business problems", "specialRequirements" : "TS/SCI with polygraph, Opt into clearance, 25% local travel", "qualificationsBasic" : "Bachelor's degree in Computer Science, 5+ years experience, Experience building models within SIGINT/Cyber operational constraints, Professional experience applying data science within Intelligence Community production chains, Experience with algorithms, Experience with data structures, Experience with parsing, Experience with numerical optimization, Experience with data mining, Experience with parallel and distributed computing, Experience with high-performance computing, Experience with neural deep learning methods, Experience with machine learning, Current, active US government Security Clearance of TS/SCI with Polygraph", "qualificationsPreferred" : "Masters or PhD Degree in Computer Science, Experience with Generative AI, Experience with Large Language Models, Experience with Signals Intelligence, Experience with Cyber Operations domains", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you excited to help the US Intelligence Community design, build, and implement artificial intelligence (AI) algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI (GenAI) methods. We build models and Machine Learning Operations pipelines for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs). Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced Data Scientists with a background in both traditional and generative AI who understand the unique challenges of the Signals Intelligence (SIGINT) and Cyber Operations domains, with experience applying data science and machine learning to transform Intelligence Community production chains. In this role, you will work at the intersection of SIGINT, Cyber Operations, and cloud computing, helping customers understand the opportunities their data presents, applying the full suite of AWS's AI/ML services to transform missions, and building solutions that earn the customer trust needed for deployment to production systems. You will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position is expected to work within the Ft. Meade/CMD location, and requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed. Key job responsibilities As a Data Scientist, you will: - Collaborate with AI/ML Scientists and Architects to research, design, develop, and evaluate AI algorithms to address real world challenges. - Participate in the design and construction of Machine Learning Operations (MLOps) pipelines and architectures. - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders. - Provide customer and market feedback to Product and Engineering teams to help define product direction. - This position may require up to 25% local travel. About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Basic Qualifications: - Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience. - 5+ years of experience in: migrating and transforming legacy SIGINT/Cyber capabilities through data science and machine learning approaches; and building models within SIGINT/Cyber operational constraints. - Professional experience applying data science within Intelligence Community production chains. - Experience with algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning. - Current, active US government Security Clearance of TS/SCI with Polygraph. Preferred Qualifications: - Masters or PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. - Experience using Python and hands on experience building models with deep learning frameworks (i.e., Tensorflow, Keras, PyTorch, MXNet). - Experience building applications leveraging GenAI. 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. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location 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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Senior Data Scientist, Data and Machine Learning, WWPS US Federal at Amazon Web Services, Inc.. 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[Mountain View, CA, USA, [Mountain View, CA, USA], Mountain View, null, CA, US]", "technicalSkills" : "SQL, Python, R, Spark, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, Tableau, Power BI, Looker", "professionalSkills" : [ "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Applied Machine Learning, Data Science, Business Intelligence, Marketing Analytics", "majorSkillsList" : [ "Applied Machine Learning", "Data Science", "Business Intelligence", "Marketing Analytics" ], "coreResponsibilities" : "Develop and deploy machine learning models, Analyze marketing campaign performance, Build and maintain data pipelines, Create dashboards and reports, Collaborate with marketing and product teams, Communicate findings to stakeholders", "teamCollaboration" : "Marketing teams; Product teams; Cross-functional teams", "domainKnowledge" : "Marketing analytics; Customer segmentation; Campaign optimization; Marketing attribution", "domainList" : [ "marketing-analytics", "customer-segmentation", "campaign-optimization", "marketing-attribution" ], "domainSpecificKnowledge" : [ "Marketing analytics", "Customer segmentation", "Campaign optimization", "Marketing attribution" ], "toolProficiency" : [ "Dbt", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake" ], "communicationSkills" : "Present findings; Communicate insights", "documentationSkills" : "Document models; Document pipelines", "problemSolvingSkills" : "Analytical thinking; Problem-solving", "qualificationsBasic" : "5+ years of experience in data science, Proficiency in SQL, Proficiency in Python or R", "qualificationsPreferred" : "PhD in a quantitative field, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), Experience with BI tools (Tableau, Power BI, Looker)", "summaryDescription" : "Business and Marketing Data Scientist, Applied Machine Learning. 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