Staff Data Engineer (L6) - Ads

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.

About the team

Ads Data Engineering is at the core of building a data ecosystem that powers Netflix's understanding and decision-making about the impact of ads on our business. This team builds rich, connected, and easily accessible data products spanning ad inventory, forecasting, targeting, ad serving, pacing, measurement, and more.

We're looking for a Staff Data Engineer to help set the technical bar for the entire Ads DE org. This isn't a role focused on a single team or domain; it's about shaping how all of our ad data systems fit together, helping different teams land on coherent, scalable approaches, and serving as a thought partner to our engineering leaders as the business and data landscape continue to evolve.

Who are you?

• A seasoned technologist with 15+ years building data-foundation, backend, or data engineering systems, someone other engineers naturally look to for direction.

• You've spent real time in advertising or ad-tech data, and while your depth may run deepest in one domain, you're comfortable moving across several.

• You've built trust and driven technical direction across organizational lines, not just within your own team, and you've done it in more than one company or role.

• You've lived through the messy middle of a major platform migration or data products’ journey from 0 to 1 and 1 to 100, and you have the scars and the instincts to show for it.

• You approach and design data as a product for the business with focus on users, quality, and measurable impact; You build data foundations as flywheels to unlock impact across the business, well beyond just orchestrating pipelines and serving analytics workflows.

• You take data privacy and governance seriously, not as a checkbox, but as something you've actually built for.

• You're a clear, thoughtful communicator who can translate technical nuance for engineers and business context for leaders, often in the same conversation.

• You're comfortable with ambiguity, and just as comfortable helping a room of smart, opinionated engineers land on a shared answer.

• You genuinely enjoy helping other engineers grow, and see that as just as core to the job as your own technical output.

What will you do?

• Set technical direction and design coherence across the entire Ads Data Engineering org, connecting the dots between domains rather than optimizing just one.

• Weigh in on and help resolve cross-domain design decisions, helping teams converge on approaches that scale across the org, not just within a single team.

• Partner closely with the Ads DE director and DE managers as a senior technical voice, bridging technical strategy with broader business priorities.

• Mentor and coach data engineers across the org, helping them grow technically and adopt AI and emerging tools and technologies.

• Build strong partnerships with senior engineers on our data platform and D&I teams, contributing to and shaping horizontal and platform-wide efforts.

• Help define what AI-native data engineering looks like for Ads DE as the function continues to evolve.

• You will be the primary technical voice in partnerships with Ads Platform Engineering, Ads Data Science, and Product; Your impact will be at the Ads level, not at the sub-domain or pipeline-level.

What (ideally) do you know?

• Modern data stacks end-to-end: ingestion, processing, storage, and serving.

• Ad-tech systems and data flows, ideally with direct exposure to domains like bidding, measurement, or attribution.

• Large-scale distributed data systems such as Spark, Kafka, or columnar stores.

• The latest in AI and agentic technologies as they apply to data engineering.

• A graduate degree in Computer Science with a data focus is a plus, as is experience formally mentoring engineers on their technical growth.

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 $510,000.00 - $820,000.00. 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.