Engineering Manager - Ads Measurement

Netflix Netflix · Big Tech · New York, NY +2 · Engineering

Engineering Manager for Netflix's Ads Measurement team, focusing on building systems to quantify campaign outcomes for advertisers. This role involves leading a team of engineers to develop first-party measurement solutions, experimentation frameworks, causal inference, attribution systems, and scalable data pipelines. The goal is to deliver impactful results for advertisers while respecting the member viewing experience.

What you'd actually do

  1. Drive success in a fast paced, flat organization with minimal process and a heavy emphasis on ownership.
  2. Support your team by contextualizing the larger vision, enabling prioritization and fostering high focus and executional excellence.
  3. Operate as an ambassador of the Netflix Culture
  4. Create a dream team by hiring, retaining, and growing high performing talent.

Skills

Required

  • 10+ years of total experience
  • 3+ years of management experience in building and leading diverse software engineering teams
  • Deep expertise in building first-party measurement solutions like conversion lift, brand lift, geo lift, and incrementality
  • designing end-to-end experimentation frameworks that produce statistically rigorous, advertiser-grade results at scale
  • Proven experience leading teams that built out causal inference and attribution systems
  • Experience building scalable data pipelines and measurement APIs that surface lift and attribution results to internal teams and external advertisers
  • strong command of the tradeoffs between measurement precision, privacy constraints, and advertiser reporting needs
  • A strong product mindset
  • experience in delivering large complex projects collaborating with a variety of cross-functional stakeholders that are technology, operations or business focused
  • General understanding of the advertising marketplace and landscape
  • Strong analytical and strategic thinking
  • demonstrated product sense and leadership in the working environment

What the JD emphasized

  • building first-party measurement solutions
  • designing end-to-end experimentation frameworks
  • causal inference and attribution systems
  • building scalable data pipelines and measurement APIs