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 Data Science and Engineering organization

Data Science and Engineering (DSE) is a key pillar of Netflix’s data-driven strategy, leveraging data, analytics, experimentation, models, and consumer insights to inform decisions. DSE focuses on data engineering, metrics, analysis, dashboards, analytic tools, experimentation research, and analytics. The team also develops models and algorithms for internal decision support.

We are committed to using data to inform our decision-making as we work toward our mission. This involves curating data across various domains, such as Growth, Finance, Product, Content, and Studio. All of this data collection and curation is made possible thanks to Netflix’s talented Data Engineers, who bring this data to life.

About Data Engineering

Data Engineering at Netflix involves building systems to process data efficiently and modeling data to power analytics. These solutions range from batch data pipelines that bring business metrics to life, to real-time processing services that integrate with our core product features. Data Engineers benefit from a strong understanding of large distributed systems on which our data solutions rely. Candidates should have experience across several of these skill sets and depth in at least one area. Effective communication skills are important, as you will collaborate with business, engineering, and data science teams to foster a culture of learning.

Member Data Engineering

The Netflix product experience helps our members discover the next great piece of content to enjoy. It could be a new series, an old movie, a live event people are talking about, or even a new video game. The product aims to present the right content, in the right format, to the right people, at the right time. When we do this well, Members value Netflix and continue to subscribe, despite the many other choices for entertainment. This team creates the data products that help measure this experience, track key metrics, and support innovation decisions through A/B testing. You will partner closely with engineering teams to refine the client and server logging that serves as a foundation for our analytic datasets, and work closely with Data Scientists and Product Managers using this data to identify new opportunities and test out new ideas.

What have you done and what do you know?

• 6 years of experience building data pipelines in batch and/or real-time settings to support a variety of use cases. Our data sources vary in size, from smaller sources to very large sources. Experience with Spark, Flink, Iceberg, and Kafka is helpful but not strictly required.
• Proficiency in Python and/or Scala for scripting, automation, and data orchestration frameworks, as well as the ability to write complex SQL (any variant) for ad-hoc and recurring workflows. You strive to write clear and maintainable code and are comfortable learning new technologies.
• Ability to model data efficiently for reporting and metrics, and to organize data for scale and fast retrieval.
• Experience sourcing and modeling data from application APIs and event streams.
• Experience converting business requirements into data engineering workstreams, enabling insights that empower colleagues to make informed decisions.
• Experience mentoring and supporting other team members, navigating ambiguity, and creating clarity.

What will you do?

• Take ownership of critical pipelines and data sets to support a variety of use cases in data science and engineering.
• Collaborate with stakeholders to understand needs, model tables using data warehouse best practices, and develop data pipelines to ensure the timely delivery of high-quality data.
• Creatively explore how to use data to continually add value to Netflix. Translate ambiguous business questions into clear data requirements, and deliver on them.
• Serve as a connector between data engineering and the business, enabling insights that empower colleagues to make informed decisions.
• Build strong partnerships with data scientists, analytics engineers, and machine learning practitioners to enable research and insight delivery for the business.

Who are you?

• Able to work both independently and collaboratively across functions (e.g., data scientists, product managers).
• Able to adapt to different work environments and see yourself as a partner in the business, with the shared goal of moving it forward.
• You have a growth mindset, are curious, authentic, self-motivated, determined, and generous in giving and receiving feedback to foster growth for yourself and those around you.
• Open to new perspectives, able to engage in thoughtful discussions, and adapt as new information emerges.
• An effective communicator who can break down and explain complex data problems in clear, concise language

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.