Data Engineer (L5) - Ads
Netflix is one of the world's leading entertainment services with 278 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages.
Data
Senior Software Engineer
Remote
5,000+ Employees
AI · Enterprise SaaS · Entertainment
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Description For Data Engineer (L5) - Ads
Netflix is seeking a Data Engineer (L5) for their Ads team. The role involves building data products to power Netflix's understanding of ad impact on their business. Key responsibilities include architecting core data products, developing large-scale data processing solutions, and partnering with various teams to create intuitive data products. The ideal candidate should have strong data intuition, analytical skills, and experience with ad ecosystems. They should be proficient in data warehousing, big data technologies, and programming languages like Python, Scala, or Java. The role offers the opportunity to work in a fast-paced, evolving environment and contribute to Netflix's growing ad-supported business model.
Last updated 8 months ago
Responsibilities For Data Engineer (L5) - Ads
- Architect, strengthen, and expand core data products that scale Netflix's Ads business
- Fully own critical portions of Netflix's Ads data products
- Collaborate with stakeholders to understand needs and model tables
- Develop large scale data processing solutions
- Partner with Analytics Engineers, Data Scientists, and Software Engineers
- Develop best practices for governance of data sets with sensitive information
- Build strong and collaborative partnerships across teams
Requirements For Data Engineer (L5) - Ads
Python
Scala
Java
- Extensive background and strong technical expertise working with data at scale
- Experience with advertising data (preferred)
- 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
- Knowledge in data modeling and establishing data architecture across multiple systems
- Ability to create understandable, simple, and clean code
- Self-direction capability given context
- Passion for data quality and delivering effective data to impact the business
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