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# Distributed Systems Engineer

- **Company:** Netflix, Inc.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $71,040.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), A/B Testing, Big Data, Cloud Foundry, Cyber Security, Data Infrastructure, Extract Transform Load (ETL), Data Stores, Data Warehousing, Distributed Computing Environment, Distributed Systems, Fault Tolerance, Machine Learning, Operational Data Store, Object-Oriented Software Development, Open Source Technology, Software Engineering, Data Processing, Multithreading, Snowflake, Apache Spark, Caching, Information Technology, Druid, Free and Open-Source Software, Presto, Restful APIs
- **Published:** October 14, 2026
- **Apply:** https://startup.jobs/distributed-systems-engineer-l4-data-platform-netflix-com-10432682

## About the Role

* You have 2+ years of experience in building large-scale distributed systems features or applications.
 * You are proficient in the design and development of RESTful web services.
 * Experienced in building and operating scalable, fault-tolerant, distributed systems
 * You are experienced in Java or other object-oriented programming languages.
 * Multi-threading is a challenge that you are comfortable tackling.
 * You have a BS in Computer Science or a related field.

## Description

We are responsible for providing the cloud-native platform for distributed data processing at Netflix. Central to analytics and data processing in Data Platform, we manage the the platform to get insights from the Exabytes-scale data in our data warehouse using Presto/TrinoDB and Snowflake. It also provides sub-second latency for real time analytics use cases as well as supports key insight dashboards using Druid. This platform enables new business initiatives such as ads and live.

Online DataStores - Composite

We offer managed datastores at scale to meet Netflix's operational data requirements across all lines of business. These datastores include various domains: Caching, Relational, Search, Key-Value, and Composite. Our focus is on developing and maintaining high-performance, reliable, and efficient datastores. Additionally, we enhance developer productivity by providing secure, intuitive and opinionated access layers. This team is passionate about building innovative, efficient, performant and scalable offerings for our customers. Our team also engages with open source communities, actively contributing to and responsibly stewarding the development and use of open source software.

Big Data Compute - Spark

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.

Storage & Movement Infrastructure

Our mission is to enable Data Movement teams to swiftly create impactful data movement solutions by providing a unified operational and security infrastructure along with comprehensive support. Our goal is to identify common challenges and offer them as foundational primitives to be leveraged by these teams. Initial set of components within the team's charter: autoscaling for compute resources, common SLIs tracking, fault management for error classification, notification, remediation, and cost efficiency., * Solving real business needs at large scale by applying your software engineering and analytical problem-solving skills.

 * Architecting and building a robust, scalable, and highly available distributed infrastructure.
 * Leading cross-functional initiatives and collaborating with engineers, product managers, and TPM across teams.
 * Sharing our experiences with the open source communities and contributing to Netflix OSS.