8 months ago
Amsterdam, NetherlandsStaff+
Responsibilities
- Design, build, and operate large-scale data pipelines for identity-linked data ingestion, transformation, and distribution.
- Architect ETL/ELT workflows using distributed computing frameworks on cloud infrastructure.
- Build API-first, platform-grade services that expose Identity capabilities as reusable self-service building blocks.
- Define observability, data quality validation, monitoring, SLAs, SLOs, and operational metrics for pipelines and services.
- Drive performance optimization, cloud cost efficiency, reliability, scalability, and reusable platform patterns.
- Own the technical evolution of probabilistic and deterministic matching, device graph construction, and audience segmentation systems.
- Architect secure data collaboration, clean room workflows, and privacy-preserving computation while applying privacy-by-design principles.
- Set technical direction, produce architecture and design documentation, and drive alignment across engineering, product, commercial, data science, and partner stakeholders.
- Lead code and design reviews, improve testing and deployment practices, and establish shared engineering standards.
- Mentor engineers and partner with the Engineering Manager on roadmap shaping, technical planning, and systemic risk resolution.
- Own end-to-end reliability, incident response, post-mortem follow-through, and continuous system health improvements.
Requirements
- 12+ years of professional software engineering experience with deep expertise in data engineering, backend systems, or distributed data infrastructure.
- Proven ability to own technical architecture end-to-end in a complex production data environment.
- Strong command of Python and SQL, with comfort using JavaScript in full-stack or API contexts.
- Extensive production experience with distributed processing frameworks such as Spark or Databricks on large-scale datasets.
- Experience with AWS and/or GCP and their core data services.
- Experience with workflow orchestration tools such as Apache Airflow, dbt, or Prefect.
- Strong familiarity with data warehousing and lakehouse architectures, including Snowflake.
- Experience building platform-grade, API-first systems for internal or external downstream consumers.
- Deep understanding of GDPR and CCPA and practical experience building privacy-compliant systems handling PII at scale.
- Familiarity with secure data collaboration, data clean rooms, or privacy-preserving computation.
- Exceptional communication, technical writing, cross-functional collaboration, mentoring, and alignment skills.
- Preferred: experience in ad tech, identity resolution, data licensing, digital media, device graphs, audience segmentation, or programmatic data flows.
- Preferred: experience with Kafka, Flink, or Spark Streaming.
- Preferred: experience incorporating AI and machine learning capabilities into production data workflows.
- Preferred: track record of cross-team technical leadership through architecture documentation, engineering standards, or mentorship programs.
Benefits
- Health insurance, wellness offerings, life and disability insurance, a retirement savings plan, paid holidays, paid time off, and other employee benefits.
- Additional rewards may include bonuses, short-term incentives, and long-term incentives.
Tech Stack
Apache AirflowApache FlinkApache KafkaApache SparkAWSDatabricksdbtGoogle Cloud PlatformJavaScriptPythonSnowflakeSQL
Categories
BackendData Engineering
About Samba
Samba builds a media intelligence and advertising platform that uses TV ACR data and cross‑platform signals to power audience measurement, targeting, and optimization for brands, agencies, and media companies. Its products support Connected TV, OTT, and digital campaigns with deterministic ad detection and addressable TV capabilities. Founded in 2018 and headquartered in San Francisco, the privately held company sells data and analytics services to help marketers plan, activate, and measure campaigns across screens.