The data infrastructure 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 as we work towards our ambitious goal of 500 million members worldwide. 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 Infrastructure Teams:
Big Data Compute | Learn More
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 Petabytes-scale data warehouse and access that data using Spark and Presto/TrinoDB. It also provides sub-second latency for a certain class of queries using Druid.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.
Big Data Orchestration | Learn More
Offers the platform for scheduling, orchestrating and executing big data jobs and workflows in a self-serve manner. These platforms include foundational services that host all ETL and ML workloads running on Big Data Systems at Netflix. These fully distributed systems are constantly evolving for Netflix scale with state-of-the-art technology. We are moving towards event-driven and intelligent orchestration which would need minimal user input/intervention.
Core Data Platform | Learn More
Core Data Platform team provides data storage as a managed service for Netflix by enhancing and operating open source data stores. This includes feature development, tooling, automation, application development and operations related to the data stores in our portfolio. Portfolio consists of a carefully curated set of both caching and persistence data stores that currently includes Cassandra, CockroachDB, Dynomite, and EVCache.
This would be your dream job if you enjoy:
- 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.
About you:
- 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.
- Note: Some of our teams in Data Platform are looking for Senior level engineers, so please see the following job posting if you think your background might align better there: Senior Distributed Systems Engineer - Data Platform
A few more things about us:
As a team, we come from many different countries and our fields of education range from the humanities to engineering to computer science. Our team includes product managers, program managers, designers, full-stack developers, distributed systems engineers, and data scientists. Folks have the opportunity to wear different hats, should they choose to. We strongly believe this diversity has helped us build an inclusive and empathetic environment and look forward to adding your perspective to the mix!
