Who are we?

Netflix is the world's leading streaming entertainment service with over 200 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.

The Content Data Engineering team, based in the entertainment capital of the world, is focused on providing our colleagues rich data so that we can make decisions on what series and films will bring the most joy to our subscribers.

We are part of a larger team that supports Netflix’s data-driven culture across marketing, streaming, product, and finance functions.  As Netflix deepens its global reach and develops more and more amazing original content, the scope and impact of our team’s work in the content space is exploding.

Netflix offers amazing co-workers, new technology, fascinating analytical and technical challenges, and a Freedom & Responsibility Culture that's truly unique

Who are you?

• Lazy in a productive way (find tedious work boring and would rather automate it).
• Charismatic, determined, curious, and industrious, and not just talented.
• Thrive in a fast paced environment, and see yourself as a partner with the business with the shared goal of moving the business forward.
• 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.
• Sharp communicator who can break down and explain complex data problems in clear and concise language. 
• Create code that is understandable, simple, and clean, and take pride in its beauty.
• Love freedom and hate being micromanaged. Given context, you're capable of self-direction.
• Passionate about data quality and delivering effective data to impact the business.  
• Motivated to explore new technologies and learn, and can do so without taking formal education.

What will you do?

• Fully own critical portions of Netflix' Content data model. Collaborate with partners to understand needs, model tables using data warehouse standard methodologies, and develop data pipelines to ensure the timely delivery of high quality data.
• Continually acquire new data sources to develop an increasingly rich dataset that characterizes content.
• Creatively explore how to use data to continually contribute to Netflix. Translate data questions into flexible methodologies that scale to answer broad problems across the organization.
• Be a bridge between data engineering and the business, enabling insight that can empower better decision-making.
• Be comfortable outside of your comfort zone - explore new tech, make your own tool, or find a new way to address an old problem.

What do you know:

• Fully own critical portions of Netflix' Content data model.  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.
• Continually acquire new data sources to develop an increasingly rich dataset that characterizes content.
• Creatively explore how to use data to continually add value to Netflix.  Translate data questions into flexible methodologies that scale to answer broad problems across the organization.
• Be a bridge between data engineering and the business, enabling insight that can empower better decision-making. 
• Build strong partnerships with data scientists, analytics engineers and 
• Be comfortable outside of your comfort zone - explore new tech, make your own tools, or find new creative ways to address an old problem.

What do you know?

• Data warehousing, data modeling, and data transformation. 
• How to write complex SQL in your sleep.
• Python for scripting and automation.
• Expert at building performant data pipelines and optimizing existing workflows for new features.
• Big Data tech - Hadoop, Spark, Pig, Hive, Presto, etc.  Significant experience with other ETL tech (Informatica, SSIS, etc) is very valuable, but expect to work in a "Big Data" environment.
• MPP/Cloud data warehouse solutions (Snowflake, Redshift, BigQuery, Vertica, Teradata, Greenplum, etc). 
• Experience with sourcing and modeling data from application APIs