Data Engineer (L5) - Ads

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships. They are seeking a Data Engineer to architect and expand the core data products that scale their Ads business, collaborating with various stakeholders to deliver high-quality data solutions.

Responsibilities:

• Architect, strengthen, and expand the core data products that scale our Ads business
• Fully own critical portions of Netflix' Ads data products
• Collaborate with stakeholders to understand needs, model tables using software engineering and data warehouse best practices, and develop large scale data processing solutions to ensure the timely delivery of high quality data
• Partner with Analytics Engineers, Data Scientists, and Software Engineers to create data products that will serve analysis, ML and reporting needs intuitively
• Develop best practices for governance of data sets with sensitive information
• Build strong and collaborative partnerships with data scientists, analytics engineers, and Machine Learning practitioners

Requirements:

• Strong technical expertise working with data at scale
• Experience with advertising data
• Understanding of how to build for privacy and business impact
• High tolerance for ambiguity and fast-changing context
• Hands-on experience building batch or streaming production data pipelines
• Experience using one or more distributed processing frameworks such as Spark, Flink or Hive/Hadoop
• Knowledge in data modeling and establishing data architecture across multiple systems
• Ability to thrive in a fast-paced environment
• Ability to create understandable, simple, and clean code
• Passionate about data quality and delivering effective data to impact the business
• Ability to collaborate with stakeholders to understand needs
• Ability to model tables using software engineering and data warehouse best practices
• Ability to develop large scale data processing solutions
• Ability to build strong and collaborative partnerships with data scientists, analytics engineers, and Machine Learning practitioners
• Domains related to advertising, data privacy, GDPR
• Data warehousing, data modeling, and data transformation for both batch and streaming
• Hands on command programming languages such as python, scala or java
• Data exploration using SQL
• Expert at building performant data pipelines and optimizing existing workflows for new features
• Experience with sourcing and modeling data from application APIs
• Team based software development tools and best practices