Data Engineer (L5)

Netflix•,

13d•$380,000 - $610,000•Hybrid

About The Position

At Netflix, our mission is to entertain the world. We are revolutionizing how shows and movies are produced, pushing technological boundaries to efficiently deliver streaming video at a massive scale over the internet, and continuously improving the end-to-end user experience with Netflix across their member journey. We pride ourselves on using data to inform our decision-making as we work towards our mission. This requires curating data across various domains such as Growth, Finance, Product, Content, and Studio. Data Engineering at Netflix is a role that requires building systems to process data efficiently and modeling the data to power analytics. These solutions can range from batch data pipelines that bring to life business metrics to real-time processing services that integrate with our core product features. In addition, we require our Data Engineers to have a rich understanding of large distributed systems on which our data solutions rely. Candidates should have knowledge across several of these skill sets and usually need to be deep in at least one. As a Data Engineer, you also need to have strong communication skills since you will need to collaborate with business, engineering, and data science teams to enable a culture of learning.

Requirements

Proficiency in at least one major programming language (e.g. Java, Scala, Python)
Comfortable working with SQL
Strong background in at least one of the following: distributed data processing or software engineering of data services, or data modeling
Familiarity with big data technologies like Spark or Flink
Comfortable working with web-scale datasets
An eye for detail, good data intuition, and a passion for data quality
Appreciation for the importance of great documentation and data debugging skills
Ability to work independently while also collaborating and giving/receiving candid feedback
Comfortable working in a rapidly changing environment with ambiguous requirements
Nimbleness and willingness to take intelligent risks

Nice To Haves

Striving to write elegant code
Comfortable with picking up new technologies independently
Enjoying helping teams push the boundaries of analytical insights, creating new product features using data, and powering machine-learning models

Responsibilities

Building systems to process data efficiently
Modeling data to power analytics
Developing batch data pipelines
Creating real-time processing services that integrate with core product features
Collaborating with business, engineering, and data science teams