Engineering Manager, Data Platform Orchestration

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 Analytics Platform and Experience (APeX)) team is responsible for providing orchestration and compute technologies to ETL and to access nearly 1 ExaByte of data in the Netflix Warehouse. It is also responsible for the underlying table format, Iceberg (an industry-standard table format and an open-source project originating in this team), metadata, security, and the data lifecycle (janitoring, compaction, etc.).

The team also owns the end-to-end development experience for data practitioners and provides scalable, self-serve analytics capabilities and platforms for Analytics Engineers and business users.

Within APeX, the Orchestration team builds and operates a reliable, cost-efficient, and easy-to-use orchestration platform that powers Netflix's analytics and machine learning workflows. We enable scheduling, orchestrating, and executing big data workflows at scale—supporting the backbone of how data is produced, transformed, and consumed across Netflix.

At the core of this platform is Maestro , our next-generation workflow orchestration system. Maestro is a fully managed workflow-as-a-service (WaaS), designed and built in-house to meet Netflix’s scale and complexity. Maestro serves thousands of users—including data scientists, data engineers, ML engineers, and software engineers—powering hundreds of thousands of workflows and millions of jobs every day.

Beyond orchestration, the team is investing in higher-level abstractions. This includes an ETL framework for incremental data processing that improves data freshness and accuracy while simplifying backfills—directly impacting cost and operational efficiency. We are also advancing intelligent operations through automated error classification and GenAI-powered remediation, leveraging systems like Pensive and Nightingale .

• Partner to deliver the vision, strategy, and adoption of current and future technologies.

• Form trusting cross-functional partnerships to align many engineering teams and ensure our solutions meet their needs, selflessly prioritizing work beyond the scope of your own domain.

• Build, scale, and grow a team of outstanding engineers, challenge them to bring their best selves to work every day, and deliver industry-leading results in stability, performance, and efficiency.

• Balance smart risks, investment in foundational technical work, paying off tech debt, and incremental improvements to deliver timely results across multiple critical strategies.

• An experienced engineering leader who can drive a team of amazing and geographically distributed engineers to do their best work while building and maintaining strong partnerships with peers and stakeholders.

• Ability to dive deep as needed to facilitate technical strategy trade-offs and zoom out to understand the big picture to shape the product.

• Experience building and running extremely reliable platform systems supporting high-scale and critical workloads, including running a 24x7 on-call, 99.95+% availability, fast response, and short mean-time-to-restore service.

• Bring rigor to decision-making and reduce ambiguity with the right mix of data collection, seeking input, farming for dissent, and making pilot investments to build understanding or confirm direction.

• Proven track record helping a team deliver timely results on critical priorities against many demands for their time, and partnering with product and engineering management to influence the right areas for investment.

• Experience building and leading software engineering teams with a focus on inclusion and diversity, ensuring that we can attract and retain the best talent from anywhere and that all voices are heard to inform our direction.

• Experience in Orchestration, Spark, Trino/Presto, Snowflake, BigQuery, RedShift, Druid, LanceDB, and/ or Big Data Analytics technologies is not a must, but very desirable.

• 100X Faster: How We Supercharged Netflix Maestro's Workflow Engine

• Evolving from Rule-Based Classifier to Machine Learning-Powered Auto Remediation

• Maestro: Data/ML Workflow Orchestrator at Netflix (Open-Source Announcement)

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 $436,000.00 - $791,000.00.