Netflix is the world’s leading streaming entertainment provider with over 260 million paid subscribers in over 190 countries around the world. This success has depended on an industry-leading engineering organization building cloud-native services with exceptional scale and resilience.

Big Data Analytics Platform (BDAP) 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 that originated in this team), metadata, security and the life-cycle of the data (janitoring, compacting etc). Two Engineering Manager roles are open in the BDAP team.

Engineering Manager, Big Data Orchestration

The Big Data Orchestration (BDO) team provides an opinionated, cost-efficient, reliable, easy-to-use orchestration platform to meet Netflix’s analytics and machine learning needs.

BDO enables scheduling, orchestrating, and executing big data workflows and jobs. The core of Orchestration is Maestro (https://netflixtechblog.com/orchestrating-data-ml-workflows-at-scale-with-netflix-maestro-aaa2b41b800c) , the next-generation Data Workflow Orchestration platform to meet Netflix's current and future needs. It is a general-purpose workflow orchestrator that provides a fully managed workflow-as-a-service (WAAS). The team built Maestro from the ground up, enabling high throughput, horizontal scalability, and advanced parametrized, event-based scheduling.

The BDO team is building an ETL framework for incremental data processing (https://netflixtechblog.com/incremental-processing-using-netflix-maestro-and-apache-iceberg-b8ba072ddeeb) for increased data accuracy, freshness, and easy backfill to directly impact the cost and operational efficiency of Analytics and ML. Orchestration is powered by the federated job execution engine, Genie (https://github.com/Netflix/genie) under the hood, which abstracts away query engine specifics from users. The suite of Orchestration products includes sophisticated error classification and intelligent job auto-remediation using Pensive and Nightingale (https://netflixtechblog.com/auto-diagnosis-and-remediation-in-netflix-data-platform-5bcc52d853d1) .

Engineering Manager, Big Data Compute Spark

The Big Data Compute Spark (BDCS) team provides high-performance, scalable, distributed data processing at rest with the customized-for-Netflix fork of Apache Spark on Hadoop to meet Netflix’s large scale data analytics and machine learning needs.

This team of 7 people (and growing) is central to batch data processing and analytics in the Data Platform at Netflix. It provides support for Spark (https://spark.apache.org/) to ETL data into the Exabytes-scale data warehouse and a variety of ways (for casual and power users) to access that data using Spark.

The team is working on integrating Spark accelerators to further drive performance, evaluating containerization platforms to run Spark, building better batch and real time observability into Spark workflows and no/low touch ways to use Spark.

This is a dream team of highly passionate and intelligent engineers who work well together. The team works on solving challenging problems at scale that have a huge impact on the Data Platform. The team has PMC members and committers who shape and contribute to open-source projects.

Check out some of our talks on Spark. (https://www.youtube.com/playlist?list=PLRLebp9QyZtaoIpE2iaF3Q8itJOcdgYoX)

What you will do:

• 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

What we are looking for:

• 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 drive down ambiguity with the right mix of collecting data, 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 and/ or Big Data Analytics technologies is not a must, but very desirable

A few more things about us:

As a team, we come from many different backgrounds and countries, and our fields of education range from the humanities to engineering to computer science and we strive to give people the opportunity to wear different hats, should they choose to. We strongly believe this diversity and agility has helped us build an inclusive and empathetic environment, and we are looking forward to adding your perspective to the mix!

Our culture is unique, and we tend to live by our values, so it’s worth learning more about Netflix here. (https://jobs.netflix.com/culture)

Blogs and Talks:

Maestro Blog (https://netflixtechblog.com/orchestrating-data-ml-workflows-at-scale-with-netflix-maestro-aaa2b41b800c)

Incremental Processing Blog

Auto Remediation Blog (https://netflixtechblog.com/auto-diagnosis-and-remediation-in-netflix-data-platform-5bcc52d853d1)

Evolving from Rule Based Classifier to Machine Learning Powered Auto Remediation

Maestro presentation at AWS Re:Invent (https://www.youtube.com/watch?v=kPYPgR0Gzrs)

Robust Foundation for Data Pipelines at Scale

Building a Scalable Workflow Scheduler with Netflix Conductor (https://www.youtube.com/watch?v=9FMk8S4vy1A)

DataWorks summit: Iceberg table format

Big Data Storage: SubSurface (https://www.youtube.com/watch?v=9uiaCN3tJyI&list=PL-gIUf9e9CCtewYqIGUKvz0fVcoyOYU1H&index=3)

Trino enjoying the view (Common Views)

Make data fluid with Apache Druid (https://www.youtube.com/watch?v=qS8XB4zHFHY)

Iceberg Right Ahead!

Compensation and Benefits

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 $190,000 - $920,000.

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 detail about our Benefits here (https://jobs.netflix.com/work-life-philosophy) .

Netflix is a unique culture and environment. Learn more here (https://jobs.netflix.com/culture) .

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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.