Distributed Systems Engineer
US$388,000 – US$619,000 / yr base salary
Posted 13 Jul 2026
Advertised as “Distributed Systems Engineer (L5) - Data Platform”
BranchFactor Summary
The original posting with the fluff stripped out
- Level
- L5
- Expected experience
- 7+ yrs
- Management level
- Individual contributor
- Employment
- Remote
| Base salary | US$388,000 – US$619,000 / yr |
|---|
CertificationsBachelor of Science
Field of studyComputer Science (or related)
Study levelBachelor's
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
The data platform teams at Netflix enable us to leverage data to bring joy to our members in many different ways. We provide centralized data platforms and tools for various business functions at Netflix, so they can utilize our data to make critical data-driven decisions. We do all the heavy lifting to make it easy for our business partners to work with data efficiently, securely, and responsibly. We aspire to lead the industry standard in building a world-class data infrastructure, as Netflix leads the way to be the most popular and pervasive destination for global internet entertainment.
We are looking for Distributed Systems Engineers to help evolve and innovate our infrastructure. We are committed to building a diverse and inclusive team to bring new perspectives as we solve the next set of challenges. In addition, we are open to remote candidates. We value what you can do, from anywhere in the U.S.
Spotlight on Data Platform Teams:
Big Data Compute {Spark}
The BDCS team is responsible for providing the cloud-native platform for distributed data processing at Netflix. This team is central to batch data processing in Data Platform. It provides support for Spark to ETL data into the Exabytes-scale data warehouse and support large scale analytics on the data to provide insight to all the Netflix functions such as A/B testing, Recommendations, Machine Learning to name a few and enable new business initiatives such as ads and live.
We are looking for exceptional talent with experience in Spark, Presto / Trino, Druid, Iceberg and distributed database systems in general. Roles in this team involve solving super interesting and challenging problems of working with data at scale, building features and performance enhancements and working closely with open source communities to shape the projects and make contributions.
Online DataStores - Caching
The Online Data Stores team is developing and maintaining highly performant, reliable, and cost-efficient data storage solutions at Netflix’s extreme scale. These data stores are built from a combination of world-class in-house solutions that are open-sourced and used by top technology firms, as well as state-of-the-art data solutions from public cloud offerings. Additionally, we enhance developer productivity by providing opinionated and intuitive, secure abstraction layers on top of the base storage systems.