Analytics Engineer 5 - Infrastructure Efficiency & Productivity

Netflix•Remote, OR

85d•$330,000 - $566,000

About The Position

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. Everything that we build to delight our members relies on our extensive technical infrastructure, which spans from services we rent from AWS to our custom-built content delivery network, Open Connect. As that infrastructure grows, so does investment in AI tooling, and understanding how efficiently we use both is central to Netflix's investment decisions. As a Senior Analytics Engineer on Platform Data Science & Engineering, you will own how Netflix understands the efficiency of its cloud and AI infrastructure. You will join a data org of Analytics Engineers, Data Engineers, Visualization Engineers, and Data Scientists who partner with engineering teams and leadership to define the metrics, build the datasets, and deliver the insights that the company relies on to spend wisely. Your work will be the trusted source of truth that engineers and executives use to make decisions about a multi-billion-dollar infrastructure footprint. This is a broad, high-visibility role with a lot of white space. You'll have the opportunity to develop metrics from scratch, build the logic and pipelines behind them, tell the story through dashboards and analyses, and turn all of it into recommendations that change how teams invest. You'll also help pioneer one of the most salient problems in the industry: quantifying the productivity impact of an increasingly AI- and agent-augmented workforce, where there is no textbook answer and real room to set the standard. The ideal candidate will excel in metric research and development, self-sufficient analytics engineering, and data storytelling, and will share a passion for continuously improving how we use data to enhance Netflix's infrastructure.

Requirements

Experienced in metric research and development in a technical domain: you build metric frameworks (not just one-off metrics) at multiple granularities that ladder up to a coherent whole, and you set targets people trust.
Self-sufficient across the full analytics loop: data exploration, cleaning, light pipeline building, business logic, and dashboards. Fluent in Python and SQL.
At home in messy, changing data, with the judgment to know when a number is right and when it needs a second look.
An exceptional communicator with both technical and non-technical audiences, experienced at telling stories with data and influencing decisions at all levels of the business.
A strong product thinker with good product sense: you get at what your partners actually need and build solutions that satisfy it.
Comfortable with ambiguity, and you thrive with minimal oversight and process.
Thoughtful about using AI in your own craft, using coding and analytics agents well, and evaluating what they produce rather than taking it on faith.

Nice To Haves

Experienced in measuring cost, efficiency, or system performance in a cloud or streaming context (a plus), or motivated to go deep in that domain.

Responsibilities

Define and own the core metrics for how Netflix understands infrastructure cost, usage, and efficiency across its compute, storage, streaming, and machine learning platforms, and expand that coverage as the footprint grows.
Help pioneer new ways to measure the productivity impact of AI tooling and autonomous agents, shaping frameworks that leadership across the company will use to guide investment.
Increase the speed and quality with which the company understands and acts on its efficiency, turning what is often slow, manual analysis into trusted, reusable insight.
Surface and size new efficiency opportunities, translating patterns in cost and usage data into recommendations that lead directly to meaningful savings.
Tell the story with data: build the dashboards, reports, and narratives that make efficiency legible to audiences from individual engineers to senior executives, partnering with our visualization engineers on the surfaces that serve them.
Partner with Data Engineers on the pipelines upstream of your metrics, and with Data Scientists on the forecasting and reliability work that connects to yours.