We are looking for a Senior Software Engineer to join our Data Integration team in Amsterdam. The Data Integration team builds and operates the platform that moves data into, through, and out of Samba TV: ingestion from clients and partners, processing and enrichment against our identity and signal layers, and distribution to downstream destinations. This is a foundational platform investment, built to scale with the next generation of data partnerships and to power agentic, self-service data workflows.
You will design, build, and operate production-grade data systems that ingest, transform, and deliver data at scale. You bring 8+ years of experience, take deep ownership of complex platform components, and work collaboratively with other senior engineers to align on technical direction. You are a trusted voice in design and architecture discussions, an active mentor, and a strong partner to adjacent teams.
What You'll Do
Data Engineering & System Development
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Design, build, and maintain reliable data pipelines for ingestion, transformation, and distribution of large-scale datasets, processing high volumes efficiently in production.
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Develop ETL/ELT workflows using distributed computing frameworks on cloud infrastructure, applying strong engineering judgment to architectural and implementation decisions within your scope.
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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.
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Implement data quality validation, monitoring, and observability for the components you own, ensuring reliability and correctness at scale.
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Contribute to platform-grade, reusable components that enable downstream teams and support self-service consumption.
Data Integration & Domain Ownership
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Take end-to-end ownership of key components within the data integration platform, ingestion, processing, or distribution, and drive their reliability, scalability, and evolution.
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Build new partner and destination integrations end-to-end, including throughput tuning, operational handoff, and contract-driven delivery.
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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.
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Engage cross-functional stakeholders, product, data science, and partner teams, to ensure the systems you build support all downstream use cases.
Technical Contribution & Collaboration
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Drive technical design for components within your scope, producing clear design documents, actively contributing to architecture discussions, and aligning the team on well-reasoned solutions.
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Conduct rigorous code reviews and uphold high standards for code quality, testability, and maintainability.
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Mentor engineers on the team through structured feedback, pairing, and design review.
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Collaborate across adjacent teams, understanding their constraints and requirements, and advocating for shared standards where applicable.
Operational Ownership
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Own the reliability of your components end-to-end, monitor their health, respond to incidents, and follow through on post-mortem improvements with rigor.
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Participate in on-call rotations and contribute actively to improving operational practices across the team.
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Drive improvements to CI/CD pipelines, deployment processes, and testing coverage for your team's systems.
Who You Are
Required
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8+ years of professional software engineering experience, with a strong focus on data engineering, backend systems, or distributed data infrastructure.
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Proficient in Python and SQL; comfortable with JavaScript in full-stack or API contexts.
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Strong hands-on experience with distributed processing frameworks (e.g., Spark, Databricks, or equivalent) working with large-scale datasets in production.
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Practical experience across AWS, GCP, and Databricks, and their core data services.
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Strong platform-thinking and API-first service design experience, building components that are reusable and consumable by downstream teams.
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Hands-on experience with streaming and event-driven data processing frameworks (e.g., Kafka, Flink, Spark Streaming, or equivalent).
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Experience building or operating multi-tenant platforms with strong isolation and security boundaries.
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Hands-on experience with workflow orchestration tools (Apache Airflow, dbt, Prefect, or equivalent).
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Experience incorporating AI and machine learning capabilities into production data workflows.
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Solid understanding of data privacy regulations (GDPR, CCPA) and practical experience building compliant systems.
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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.
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An active mentor, you invest in others, give direct feedback, and care about raising the bar for the team as a whole.
Preferred
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Strong familiarity with data warehousing and lakehouse technologies, with a preference for Snowflake.
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Exposure to ad tech, audience activation, data licensing, or digital media, familiarity with concepts such as device graphs, audience segmentation, identity resolution, or measurement.