Technical Program Manager 6 - Games Data Science & Engineering

Netflix Netflix · Big Tech · United States · Remote · Engineering Operations

Netflix is seeking a Technical Program Manager 6 for their Games Data Science & Engineering team. This role will drive programs related to data pipelines, telemetry, experimentation, and analytics tools for game development. The TPM will partner with data scientists, data engineers, and platform engineers to ensure data systems are reliable, scalable, and impactful. The role requires technical fluency in data engineering and analytics domains, strong communication skills, and experience managing complex, multi-stakeholder programs.

What you'd actually do

  1. Own end-to-end program delivery for Games Platform DSE initiatives, including telemetry instrumentation, data pipeline development, metrics infrastructure, and the systems that power game quality and performance measurement.
  2. Serve as the TPM interface between Games DSE and game studio partners, internal and external, ensuring studios have the data tools, dashboards, and analytical support they need to understand and improve their games on the Netflix platform.
  3. Drive programs that deliver experimentation infrastructure for games, A/B testing frameworks, holdout methodology, experiment configuration tooling, enabling both platform and studio teams to run rigorous, statistically valid experiments.
  4. Develop a working understanding of the Games data architecture, telemetry ingestion, data warehouse patterns, event schemas, pipeline orchestration, sufficient to identify technical risks and evaluate trade-offs without needing full translation from engineers.

Skills

Required

  • technical program management
  • data engineering
  • data science
  • analytics
  • data pipelines
  • telemetry architectures
  • experimentation frameworks
  • analytical tooling
  • systems thinking
  • communication
  • risk management
  • collaboration

Nice to have

  • familiarity with experimentation platforms
  • A/B testing methodology