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Analytics Engineer 5 - Ads Technical Measurement and Quality

Netflix LogoNetflix
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Salary

Annual salary: $330,000.00 - $566,000.00

Location

USA - Remote

Posted

Today

We want to provide a seamless, high-quality advertising experience for members across devices and advertising formats. Supporting such a broad range of experiences requires intricate coordination of systems behind the scenes across ads serving infrastructure, content delivery platforms, and client-side rendering. Our Client Data Science & Engineering team uses some of Netflix’s largest datasets to generate insights about the end-to-end advertising experience and the systems that underpin it. Our end goal is to drive higher-quality experiences across the variety of devices and networks our global members use. We’re looking for an analytics engineer to uplevel our quality of experience (QoE) instrumentation for Netflix ads, shepherding it from telemetry on user devices all the way through to high-visibility dashboards that are used by our engineering and business teams to monitor and improve the Netflix experience.

In this role, you will

  • Be at the forefront of using analytics and data engineering skills to ensure that advertising QoE data can be used effectively across the company.
  • Act as the core steward of ads QoE, focusing on instrumentation, monitoring, understanding the user experience as it evolves within our product, and influencing best practices for producers and consumers.
  • Collaborate with product engineering teams, data engineering, and data scientists to develop new ways of measuring how users perceive performance.

To be successful in this role, you have

  • Passion for exploring and building highly technical datasets and logging.
  • Experience with creating clear written and visual technical documentation of user flow and how it is instrumented.
  • Exceptional spoken and written communication with technical and non-technical audiences; highly effective at developing meaningful stakeholder relationships and deep domain expertise.
  • High fluency in SQL and proficiency with Python, along with experience building data pipelines.
  • Familiarity with software engineering practices (experience with data processing and tool development at scale is a plus).
  • Comfort with ambiguity; ability to thrive with minimal oversight and process.

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