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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.

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.

The Ads Business Analytics & Tools team builds the analytical foundation that powers the Ads business — metrics, semantic models, analytic tools, and governed data products. We own the Ads Metric Catalog (AMC), the semantic layer that defines every core Ads metric once and materializes it across all analytical surfaces. Our goal is to help Netflix scale its advertising platform with trust and clarity.

We're looking for a Senior Analytics Engineer to own the analytics foundation for advertiser-facing reporting and help drive shared metric consistency across the ad platform. The reporting module is the primary focus. It's the most visible surface on the ad platform — what advertisers see, what gets audited, and what sets the bar for how every other module approaches metrics. The module is growing as we expand into regulatory compliance reporting for international markets, partner-built reports, and new report types for an increasingly global advertiser base. You'll own reporting's analytics foundation — the semantic layer, metric methodology, and analytical data contracts — and in doing so, establish a reference implementation that other modules can follow. As the platform scales, the accuracy and consistency of what advertisers see in reporting is central to the product experience.

The ad platform backend is also evolving quickly, with new modules being developed that often share metrics with the reporting system. Netflix's ad platform powers campaign management, delivery, yield analytics, billing, and reporting through a suite of interconnected modules — and that suite keeps expanding. This role helps ensure metric definitions stay consistent across all of them.

You'll work at the intersection of our Ads Metric Catalog and the platform's operational metric computation layer. AMC defines metrics once on the analytical side and materializes them across dashboards, BI tools, and reporting surfaces. The ad platform has its own computation layer that powers real-time delivery, pacing, and reporting. Both consume the same underlying data but serve different latency and computation requirements — making cross-system metric consistency an ongoing, hands-on effort.

What You Will Do

• Go deep on reporting. Serve as the dedicated Analytics Engineer for the platform's campaign reporting capabilities — default reports, new report builds (e.g., billed cost reports), partner-built reporting modules (e.g., regulatory compliance reporting for international markets), and the data models that power them. This module is expanding, and the scope will grow with it. You'll work closely with the Campaign Reporting PM on prioritization and roadmap, and with DE on schemas and data contracts.

• Go wide on metric standards. Act as the steward for cross-module metric consistency in partnership with Product, DE, Finance, and other module owners. Reporting is the reference implementation — your metric definitions, source dataset choices, and calculation methodologies serve as the benchmark against which other modules align. That said, the platform is evolving, and new modules will bring new questions about how metrics should be defined. Part of the job is working through those questions with module teams as they come up — ideally early, when they're designing new metrics or data models, so the reference patterns are part of their build process rather than a retrofit.

• Build and extend the Ads Metric Catalog into the ad platform. As a member of the team that owns AMC, you'll contribute directly to the semantic layer — writing metric definitions, building materialization logic, and developing governance workflows. You'll help ensure reporting is a flagship consumer of AMC-governed metrics and build adoption patterns that other modules can follow.

• Partner closely with the Campaign Reporting PM. The PM defines what the product should do. You define how the metrics that power it are calculated, validated, and governed. As the platform scales for external advertisers, that partnership is where product vision meets data rigor.

• Partner with Data Engineering on Data Foundations. Work with the Reporting DE lead to ensure metric standards are embedded in the ongoing backend rearchitecture — shared data models, consolidated reporting schemas. Reporting is the primary proving ground for this rearchitecture, and the patterns you establish here will shape how newer modules build their data foundations.

• Float across the platform as needed. When other modules need AE support — reviewing data models against the shared schema, validating new metrics, or ensuring they follow the patterns reporting has established — you step in. As the ad platform evolves, this kind of cross-module support becomes more important, not less.

• Participate in cross-functional governance. Represent the reporting and metric standards perspective on cross-team councils and platform federation processes — reviewing specs, contributing to data standards, and helping ensure metric consistency between analytical and operational surfaces alongside DE, Product, and Platform Engineering partners. As new modules come online and existing ones evolve, you'll help ensure metric definitions stay aligned — surfacing questions early and working with the relevant teams to resolve them.

What You Bring

• Full-stack data fluency. SQL, Python, and experience with semantic modeling and metric computation. Exposure to columnar analytics stores (e.g., Druid) and lakehouse architectures (e.g., Iceberg) is valuable — deep expertise in at least one analytical data platform is needed for the role.

• Metric governance experience. Familiarity with semantic modeling (LookML, DataJunction, or equivalent) and data quality frameworks. You understand that defining a metric across a matrixed organization is as important as writing the code to compute it.

• A product-minded approach to metrics. You're comfortable with ambiguity, partner closely with PMs and DEs, and can drive consensus on metric definitions across Product, Engineering, and Analytics teams. You think like a technical lead for the semantic layer — not just building it, but shaping how others use it.

• Communication and influence. The ability to work with PMs, DEs, and AEs across module teams on shared definitions and standards. You connect the dots between what the numbers say and what they should mean.

• Workflow orchestration. Experience with tools like Apache Airflow or Maestro, and analytics scripting for building and maintaining data pipelines.

• API fluency. Familiarity with API design, querying, and integration (e.g., GraphQL, REST) — we're building out both external and internal APIs for querying data and serving metric definitions, and this role will increasingly intersect with those systems.

• Interest in AI and agentic workflows. We're investing in how AI can accelerate metric governance, data quality, and self-serve analytics. This role will intersect with that work, so curiosity about how LLMs, agents, and AI-powered tooling can improve analytics workflows is valuable.

• Awareness of external data quality standards (e.g., MRC) is a plus — our reporting surfaces serve external advertisers and operate under strict data integrity expectations.

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $330,000.00 - $566,000.00. This compensation range will vary based on location.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.