Manager, Data Engineering

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.

Content Promotion & Distribution Data Engineering team helps enable and inform how we launch, promote, and distribute Netflix content across surfaces, channels, and markets. When a Netflix member opens our app, visits a partner device, or encounters our campaigns off-service, we have a few precious moments to help them choose a story that is right for them at that moment in time. Presenting compelling evidence — artwork, trailers, synopses, notifications, and marketing assets — that authentically represent each title and resonate with the member is essential to this effort.

We also work to ensure these experiences scale globally across languages, devices, and distribution channels.

Data and insights are at the heart of how we make these decisions. Our role in Data Engineering is to make this possible: to provide robust, scalable, and well-modeled tabular and multi‑modal data foundations that power analytics, experimentation, and machine learning across the Content Promotion & Distribution ecosystem.

We are looking for a seasoned leader to manage our Content Promotion & Distribution Data Engineering team.

The Team:

Owns core analytical data models and pipelines that power reporting, decision-support, and experimentation

Builds and operates multi‑modal data foundations (e.g., text, metadata, image, video, and audio) for ML and GenAI model development and evaluation

Partners closely with Content Promotion and Distribution DSE, AI and Data Platform, Content Engineering to build and steward complex data and media pipelines, and to set best practices for data storage, access, and usage by analytics engineers, data scientists, and software/ML engineers.

As a leader in this space, you will…

Hire, lead, and develop a stunning team of Data and ML Engineers across a heterogeneous skill set (data, software, and ML engineering).

Own the end-to-end data foundations for Content Promotion & Distribution, spanning traditional data engineering craft (batch/streaming pipelines, data modeling, data warehousing, data quality, and reliability for analytics and experimentation) and multi‑modal, ML‑ready data (media, text, and rich metadata pipelines that prepare data for training and serving ML and GenAI models).

Partner with cross-functional leaders across Content Promotion & Distribution DSE, AI ML Platform, Content Engineering, Studio Algo, and Marketing to ideate, prioritize, and execute on high-impact data products and tools.

Steer deeply impactful work on foundational data and media products that support Netflix's Content Promotion & Distribution, spanning agentic solutions, multimodal media understanding, and generation, including title launch management and promotional planning, analytics and optimization for promotional media, content media and ML foundations, and emerging GenAI/ML use cases in promotion and creative automation.

Provide technical vision and strategy for how we model, store, transform, and serve both structured and multi‑modal data to power analytics, experimentation, and ML at scale.

Balance near-term and long-term needs, from ongoing support of stakeholder quarterly goals to multi-year investments in infrastructure and "paved paths" for ML/GenAI research and productionization.

Set and raise the technical bar for data engineering craft in this space.

Drive alignment in ambiguity by clarifying trade-offs, making principled decisions, and bringing diverse partners along a shared roadmap.

Grow and mentor the team through thoughtful observation, coaching, and courageous, honest feedback.

Build both software and social glue across a wide network of stakeholders—VPs, Directors, Managers, and ICs.

This role may be for you if…

You have been leading data engineering teams for 7+ years, including managing managers and larger, heterogeneous teams (data, software, ML engineers) or shared-resource teams.

You have a proven track record leading innovative, influential data engineering work in complex business domains, ideally involving multimodal media data marketing/promotion, content/media, experimentation, and or ML/AI-driven products.

You are comfortable owning the technical quality of both analytics-focused data engineering (ETL/ELT, modeling, warehousing, data quality) and ML-focused data engineering (feature pipelines, media and multi‑modal data preparation, training/serving data sets).

You are a crisp communicator who develops strong relationships with a wide variety of stakeholders and can drive alignment across Director/Manager-level partners.

You are deeply invested in creating an inclusive team environment and helping each team member grow.

You have experience leading a team of shared resources, effectively prioritizing and sequencing work across multiple domains and stakeholder groups.

You are an experienced partner for ML Platform, Content Engineering, and Data Platform teams.

You have deep technical expertise in one or more aspects of data engineering, such as media or other large-scale, multi‑modal asset processing pipelines, building ML- and experimentation-ready data products, data warehousing and dimensional/semantic data modeling, and batch and streaming data processing.

You're comfortable with a collection of Big Data and cloud-based tech (e.g., S3 or similar object storage, Spark or other distributed processing frameworks, modern data warehouses, workflow orchestration).

You are curious, reflective, humble, and impact-oriented.

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. The range for this role is $446,000.00 - $752,000.00.

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.

• 7+ years leading data engineering teams, including managing managers and diverse skill sets (data, software, ML engineers).
• Proven expertise in analytics and ML-focused data engineering, including multi-modal media data pipelines and data warehousing.
• Strong communication and partnership skills with cross-functional leaders and experience prioritizing work across multiple domains.