What You'll Do
Design and build reliable data pipelines for ingestion, transformation, and distribution of large-scale datasets, making sound architectural decisions within your scope.
Develop ETL/ELT workflows using distributed computing frameworks on cloud infrastructure, applying engineering judgment to design and implementation decisions within your scope, partnering with senior engineers on broader architecture.
Build API-first services that expose ingestion, processing, and distribution capabilities to internal teams and external consumers, with attention to reliability, clear contracts, and ease of integration.
Implement data quality validation, monitoring, and observability for the components you own, ensuring reliability and correctness in production.
Build reusable platform components with a clear understanding of how they serve downstream consumers.
Data Integration & Domain OwnershipTake ownership of components within the data integration platform, ingestion, processing, or distribution, and drive their reliability and iteration.
Build partner and destination integrations end-to-end, including throughput tuning and operational handoff.
Apply GDPR, CCPA, and Samba data governance requirements to the systems you build.
Collaborate with immediate team members and engage with adjacent teams to understand downstream use cases.
Technical Contribution & CollaborationDrive technical design for components within your scope, producing design documents and participating actively in architecture discussions.
Conduct code reviews and uphold strong standards for code quality, testability, and maintainability across the team.
Build working relationships with adjacent teams and reason about cross-functional requirements.
Operational OwnershipOwn the reliability of your components, monitor their health, respond to incidents, and follow through on post-mortem improvements.
Participate in on-call rotations and contribute to improving operational practices across the team.
Build and maintain CI/CD pipelines, deployment processes, and testing coverage for team systems.
Who You Are
5+ years of professional software engineering experience with a Bachelor's degree in Computer Science, Software Engineering, or a related technical field (or 3+ years with a Master's, a PhD with no prior experience, or equivalent), with a meaningful focus on data engineering, backend systems, or distributed data infrastructure.
Proficiency in Python and SQL; ability to write clean, well-tested, production-ready code.
Hands-on experience with distributed processing frameworks (e.g., Spark, Databricks, or equivalent) in production.
Hands-on production experience building cloud-native data systems on AWS, GCP, or Databricks, including their core data services.
Experience building API-first services with a focus on correctness and reliability.
Working experience with streaming or event-driven data processing frameworks (e.g., Kafka, Flink, Spark Streaming, or equivalent).
Experience with workflow orchestration tools (Apache Airflow, dbt, Prefect, or equivalent).
Familiarity with data privacy regulations (GDPR, CCPA) and an understanding of how they affect system design.
A clear communicator who participates actively in design discussions, shares context proactively, and works well across a team. Comfortable advising more junior engineers on technical matters within your area.
PreferredFamiliarity with data warehousing and lakehouse technologies, with a preference for Snowflake.
Experience building or operating multi-tenant data platforms.
Experience with AI/ML integration in production data workflows.
Exposure to ad tech, audience activation, data licensing, or digital media — familiarity with concepts such as device graphs, audience segmentation, identity resolution, or measurement.
Skills Required
- 5+ years of professional software engineering experience
- Bachelor's degree in Computer Science, Software Engineering, or related field
- Proficiency in Python and SQL
- Experience with distributed processing frameworks
- Hands-on production experience with cloud-native data systems
- API-first services development experience
- Experience with streaming or event-driven data processing frameworks
- Experience with workflow orchestration tools
- Familiarity with GDPR, CCPA
What We Do
Television remains a vibrant cultural influence and an essential source of entertainment and information worldwide. Tremendous growth in content choices, and viewing platforms that allow us to watch anything, anytime, on any screen, has actually made it harder for viewers to discover and keep up with all the great programming available. It’s also more competitive for content providers to keep your attention, and for marketers to make strong, measurable connections with their target consumers. Technology that improves the viewing experience, enables content discovery, and addresses audience fragmentation across screens will strengthen television’s business model and relevance to consumers. Data is at the center of any solution to make TV better. Samba TV's technology is built into Smart TVs and easily maps to smart phones and tablets. By recognizing what's on screen, Samba TV learns what viewers like and using machine learning algorithms, enables discovery of shows and actors in a whole new way. Likewise, our data and measurement products are transforming the way stakeholders across the media landscape are thinking about their business. Given the dramatic growth in streaming services, connected devices, time-shifting, and multi-screen viewership, our data products solve real problems and create a meaningful competitive advantage for our clients.
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