Netflix is the world’s leading internet streaming service with over 250 million members in 190 countries. Our members enjoy a wide variety of streamed videos per day, using over 1000 types of devices, generating more than a third of downstream Internet traffic in North America. The Content Knowledge Graph team within Data Science & Engineering equips scientists, engineers, and business executives with a global understanding of the entertainment industry “on & off-service”. Our flagship product is the Netflix KG (“Hitch”), a data and analytics foundational layer, that is a data pillar for 100s of diverse use cases across Netflix: from enabling content and marketing business executives to make better data-driven decisions to equipping AI/ML scientists with signals that power billions of daily predictions, to providing key inputs to engineering teams building business-critical applications. Hitch is a foundation for innovation that is helping to fuel Netflix’s long-term growth.
We are looking for a Data Engineer to own and scale our data quality system while supporting high-visibility data pipelines and products. As part of this team, you will work on a diverse tech stack to build insightful, scalable, and robust data systems that describe the entities, interactions, and usage patterns across the Netflix Knowledge Graph.
The ideal candidate will have a strong background in distributed data processing, demonstrate strong data intuition and analytical thinking, and share our passion for continuously improving the reliability and trust in Hitch.
Who you are:
- Obsessed data quality: build reliable and trustworthy web-scale data products
- Highly proficient in at least one of programming language (e.g. Python, Java, or Scala) with at least 2 years of software/data engineering experience
- Comfortable with advanced SQL and using big data technologies (e.g. Hive, Presto, Spark, Iceberg, etc) on medium to large-scale data sets
- Conceptually familiar or interested in learning graph technologies (e.g. databases, data models, query languages)
- You have strong communication skills and can collaborate with cross-functional team members and partners on projects that drive high-impact outcomes
- Excited about learning new business domains, demonstrating excellence, and growing your career
What you will do:
- Engineer efficient, adaptable and scalable data pipelines to process structured and unstructured data
- Build robust data quality systems using best-in-the-class techniques and technologies enabling the team and partners to deliver more business value
- Develop a deep understanding of the Netflix Data Science & Engineering ecosystem and related business domains
- Understand business requirements and provide data which empowers teams to innovate on top of the Netflix KG
- Join a stunning team of data and machine learning engineers with diverse skill sets, partnering closely with data science, analytics, and business counterparts
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 $170,000 - $720,000.
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.
Netflix is a unique culture and environment. Learn more
here.
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.
