Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
The reach of Netflix and the fandom we create fuels the “Netflix effect” - a virtuous cycle of great content and intense fandom that catapults our stories into the cultural conversation. Netflix influences what people around the world search for and talk about, the music they listen to, the books they read, the countries they visit, and how they dress.
Our marketing efforts help to kick start the Netflix effect, and we are providing more and more ways for fans to engage with our stores: Tudum, events like Netflix Bites and Bridgerton experiences, and the launch in 2025 of the first two Netflix House locations.
Netflix is a data-driven company, and we are hiring multiple data engineers to increase our data support for marketing and fandom activities around the world. The opportunity for impact in these roles is enormous: Netflix social media channels generate more than 100B impressions a year, we are expanding fandom into the real world, and we’ve barely scratched the surface of the data available to support these activities.
What have you done and what do you know?You have 8+ years of experience and proficiency building data pipelines in both batch and real-time settings, to support a variety of use cases. Some of our data sources are small (e.g., sales at Netflix House), and some are enormous (e.g., social media feeds). Our stack is Spark, Flink, Hive/Iceberg, Kafka - experience with these specific technologies is helpful, but not strictly required.
You are proficient in Python for scripting, automation, and data orchestration frameworks, and you can write complex SQL (any variant) for ad-hoc and recurring workflows. You strive to write elegant and maintainable code, and you're comfortable picking up new technologies.
You understand how to model data efficiently for reporting and metrics, and how to organize data for scale and fast retrieval.
You have experience sourcing and modeling data from application APIs.
You’ve worked with common data warehouse solutions, such as Snowflake, Redshift, BigQuery, Vertica, Teradata, Greenplum, etc.
Fully own critical pipelines and data sets to support Netflix efforts around marketing and fandom.
Directly 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 then deliver on them.
Be a bridge between data engineering and the business, enabling insights that empower our colleagues to make better and more informed decisions.
Build strong partnerships with data scientists, analytics engineers, and machine Learning practitioners to enable research and insight delivery for the business.
You want to live and breathe the Netflix Culture. Our ways of working are different, and you are excited to embrace and contribute to our culture.
You work quickly and independently while also collaborating effectively across functions (e.g. with marketing experts, data scientists, product managers).
You thrive in a fast paced environment, and see yourself as a partner with the business with the shared goal of moving the business forward.
You have a growth mindset, and expect the same from your colleagues. Not only talented, you are also curious, authentic, selfless, determined, and industrious. You generously give and receive candid feedback, to grow yourself and those around you.
You have strong beliefs that are weakly held: you can deliberate and hear all sides of a discussion, and adapt to new perspectives that emerge from it.
You are a sharp communicator who can break down and explain complex data problems in clear and concise language.
You are comfortable getting outside of your comfort zone, to explore new tech, make your own tools, or find new creative ways to address an old problem.
Netflix offers amazing co-workers, new technology, fascinating analytical and technical challenges, and a Culture that's truly unique.
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.
Skills Required
- 8+ years building data pipelines in batch and real-time
- Proficiency in Python for scripting, automation, and orchestration
- Ability to write complex SQL for ad-hoc and recurring workflows
- Experience modeling data for reporting and metrics at scale
- Experience sourcing and modeling data from application APIs
- Experience with common data warehouse solutions (Snowflake, Redshift, BigQuery, Vertica, Teradata, Greenplum)
- Experience with Spark, Flink, Hive/Iceberg, Kafka
- Strong collaboration and communication with stakeholders, data scientists, and analytics engineers
Netflix Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netflix and has not been reviewed or approved by Netflix.
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Fair & Transparent Compensation — Compensation is positioned as “personal top of market” with regular recalibration and broad posted ranges for senior roles that signal the philosophy. The cash‑forward structure and clearly described pay‑mix choices help set expectations on how pay is determined.
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Equity Value & Accessibility — Employees can choose the mix of cash versus fully vested 10‑year stock options, with grants structured to be retained even after departure. This employee‑directed design increases accessibility and control over equity participation.
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Healthcare Strength — Health coverage is described as comprehensive across medical, dental, vision, and mental health, with employer funding designed to offset premiums. Additional resources like counseling/coaching and wellness support reinforce breadth in care access.
Netflix Insights
What We Do
Netflix is the world's leading streaming entertainment service with 209 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.








