Data Engineering Intern, Data Science and Engineering

Who are we?
Netflix is the world's leading streaming entertainment service with 195+ million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Netflix is reinventing entertainment from end to end. We are revolutionizing how shows and movies are produced, pushing technological boundaries to efficiently deliver streaming video at massive scale over the internet, and continuously improving and personalizing how content is presented around the globe.

Data Science and Engineering(DSE) team at Netflix is aimed at improving various aspects of our business.  Data Engineers within DSE, are focused on providing our colleagues rich data so that we can make decisions on how to bring the most joy to our subscribers via compelling content, personalized product interactions, and stellar customer service. As well as building datasets to better understand and continuously improve efficiency in studio productions, platform utilization, and membership growth. Data Engineering function is foundational to  the success of those areas and is an exciting space to gain hands-on experience with new technologies and unique culture.

Who are you?

• Curious and motivated learner - competing an MS/PhD degree in Computer Science, Engineering, Math, Statistics, graduating in Winter 2021 or Summer 2022
• Clear communicator - you are concise and articulate in speech and writing
• Coursework or some experience with data structures and dimensional data modeling, ETL, data warehouse architecture
• Understand principles of distributed systems (Hadoop, Spark, MPP)
• Practical knowledge of scripting languages (ideally Python or Scala)
• Able to write a SQL query with minimal guidance

What will you learn?

• Build large-scale batch and real-time pipelines with data processing frameworks like Spark or Flink
• Collaborate on designing components of analytical data model
• Design technical and business driven data audits to ensure data quality
• Monitor and troubleshoot data issues in the data pipelines
• Collaborate with other Data Engineers and build relationships with Analytics and ML Engineers, and Data Scientists
• Learn how to work closely with business stakeholders in a high paced environment