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Strong employer brand with senior, specialized data role and niche ad-tech skills.
Core data engineering skills transferable, but ad-tech RTB and privacy expertise increases domain specificity.
Explicit 8+ years and 4+ years data engineering plus many mandatory platform technologies.
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Own and deliver end-to-end data pipelines and data lakehouse for real-time and batch processing of advertising bid-stream events at scale.
Architect and develop backend DSP microservices including bidding, pacing, budget management, and reporting with reliability and low latency.
Lead and mentor a data engineering team, manage technical roadmap, collaborate with ML, product, and growth teams for data-driven competitive advantage.
8+ years software engineering experience, including 4+ years in data engineering or large-scale data systems.
Strong expertise in distributed stream processing technologies (Kafka, Flink, or Spark Structured Streaming) and petabyte-scale SQL.
Hands-on experience with real-time analytical DBs (StarRocks, Snowflake, or ClickHouse) and orchestration tools (Airflow, Prefect, or Dagster).
Proficiency in Python and/or Java/Scala, REST/gRPC microservices, Kubernetes, and CI/CD; understanding of RTB ecosystem and privacy regulations (GDPR/CCPA).
Experienced technical leader comfortable owning and scaling real-time data infrastructure in an ad-tech or programmatic advertising environment.
Deep familiarity with DSP/RTB systems, real-time analytics databases, and building low-latency, reliable backend services.
Proven ability to lead engineering squads from ambiguous requirements to production while partnering cross-functionally with ML, product, and growth teams.