Samba
media intelligence
SeniorSoftwareEngineer-DataIntegration
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer - Data Integration at Samba. Skills: Data Engineering, System Development, Data Integration, backend systems, distributed data infrastructure, Python, JavaScript, distributed processing frameworks, cloud infrastructure, API-first service design, streaming and event-driven data processing, workflow orchestration tools, AI and machine learning integration, data privacy regulations. Design, build, and maintain reliable data pipelines for ingestion, transformation, and distr”
What You'll Achieve.
ensure the systems you build support all downstream use cases; uphold high standards for code quality, testability, and maintainability; raising the bar for the team as a whole; ensuring reliability and correctness at scale
Industry & Context.
Participate in on-call rotations
What They're Looking For.
Must Have
8+ years of professional software engineering experience, with a focus on data engineering, backend systems, or distributed data infrastructure, Proficient in Python, comfortable with JavaScript in full-stack or API contexts, hands-on experience with distributed processing frameworks (e. g. , Spark, Databricks, or equivalent) working with large-scale datasets in production, Practical experience across AWS, GCP, and Databricks, and their core data services, platform-thinking and API-first service design experience, building components that are reusable and consumable by downstream teams, Hands-on experience with streaming and event-driven data processing frameworks (e. g. , Kafka, Flink, Spark Streaming, or equivalent), Experience building or operating multi-tenant platforms with isolation and security boundaries, Hands-on experience with workflow orchestration tools (Apache Airflow, dbt, Prefect, or equivalent), Experience incorporating AI and machine learning capabilities into production data workflows, Solid understanding of data privacy regulations (GDPR, CCPA) and practical experience building compliant systems, A clear communicator and cross-functional collaborator, able to articulate technical decisions, engage constructively in design reviews, and navigate complex stakeholder relationships outside your immediate team, An active mentor, you invest in others, give direct feedback, and care about raising the bar for the team as a whole
Nice to Have
familiarity with data warehousing and lakehouse technologies, with a preference for Snowflake, Exposure to ad tech, audience activation, data licensing, or digital media, familiarity with concepts such as device graphs, audience segmentation, identity resolution, or measurement
What You'll Do.
and maintain reliable data pipelines for ingestion
and distribution of large-scale datasets
Develop ETL/ELT workflows using distributed computing frameworks on cloud infrastructure
Design and build API-first services that expose ingestion
and distribution capabilities
Implement data quality validation
and observability for the components you own
Contribute to platform-grade
Take end-to-end ownership of key components within the data integration platform
Build new partner and destination integrations end-to-end
Design and implement privacy-compliant data handling practices
Engage cross-functional stakeholders
Drive technical design for components within your scope
Conduct rigorous code reviews
Mentor engineers on the team
Collaborate across adjacent teams
Own the reliability of your components end-to-end
Follow through on post-mortem improvements
Participate in on-call rotations
Contribute actively to improving operational practices
Drive improvements to CI/CD pipelines
How You'll Work.
Team & Collaboration
Engage cross-functional stakeholders, product, data science, and partner teams; Collaborate across adjacent teams, understanding their constraints and requirements, and advocating for shared standards where applicable; Articulate technical decisions; Engage constructively in design reviews; Navigate complex stakeholder relationships outside your immediate team; Invest in others; Give direct feedback; Care about raising the bar for the team as a whole
Communication Scope
clear communicator; articulate technical decisions
Full Job Description
## Description Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant. ## What You'll Do Data Engineering & System Development Design, build, and maintain reliable data pipelines for ingestion, transformation, and distribution of large-scale datasets, processing high volumes efficiently in production. Develop ETL/ELT workflows using distributed computing frameworks on cloud infrastructure, applying strong engineering judgment to architectural and implementation decisions within your scope. Design and build API-first services that expose ingestion, processing, and distribution capabilities to internal teams and external consumers, with a focus on reliability, clear contracts, and ease of integration. Implement data quality validation, monitoring, and observability for the components you own, ensuring reliability and correctness at scale. Contribute to platform-grade, reusable components that enable downstream teams and support self-service consumption. Data Integration & Domain Ownership Take end-to-end ownership of key components within the data integration platform, ingestion, processing, or distribution, and drive their reliability, scalability, and evolution. Build new partner and destination integrations end-to-end, including throughput tuning, operational handoff, and contract-driven delivery. Design and implement privacy-compliant data handling practices, applying GDPR, CCPA, and Samba's data governance policies, including support for clean room and privacy-preserving data collaboration workflows. Engage cross-functional stakeholders, product, data science, a
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