Samba
media intelligence
SoftwareEngineer-DataIntegration
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optimal for Senior candidates.
“Software Engineer - Data Integration at Samba. Skills: Data Engineering, System Development, Data Integration, Backend Systems, Distributed Data Infrastructure, Cloud-native data systems. Design and build reliable data pipelines for ingestion, transformation, and distribution of large-scale datasets. Develop ETL/ELT workflows using distributed computing frameworks on cloud infrastructure”
What You'll Achieve.
Ensure reliability and correctness in production; Drive reliability and iteration of owned components; Ensure reliability and correctness in production
Industry & Context.
Engineering judgment; Sound architectural decisions
Participate in on-call rotations
What They're Looking For.
Must Have
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 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.
Nice to Have
Familiarity 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.
What You'll Do.
Design and build reliable data pipelines for ingestion
and distribution of large-scale datasets
Develop ETL/ELT workflows using distributed computing frameworks on cloud infrastructure
Build API-first services that expose ingestion
and distribution capabilities
Implement data quality validation
and observability for the components you own
Build reusable platform components
Take ownership of components within the data integration platform
and drive their reliability and iteration
Build partner and destination integrations end-to-end
and Samba data governance requirements to the systems you build
Drive technical design for components within your scope
Produce design documents
Participate actively in architecture discussions
Uphold standards for code quality
and maintainability across the team
Build working relationships with adjacent teams
Reason about cross-functional requirements
Own the reliability of your components
Follow through on post-mortem improvements
Participate in on-call rotations
Contribute to improving operational practices across the team
Build and maintain CI/CD pipelines
and testing coverage for team systems
How You'll Work.
Team & Collaboration
Partnering with senior engineers on broader architecture; Collaborate with immediate team members; Engage with adjacent teams to understand downstream use cases; Participate actively in architecture discussions; Uphold standards for code quality, testability, and maintainability across the team; Build working relationships with adjacent teams; Reason about cross-functional requirements; Contribute to improving operational practices across the team
Communication Scope
Clear communicator; Participates actively in design discussions; Shares context proactively
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 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 Ownership Take 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 & Collaboration Drive technical design for components within your scope, producing design documents
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