Distributed Systems Engineer (L4) - Data Platform
Los Gatos, California /
Streaming – Data Platform Engineering /
Full-time
/ On-site
At Netflix, we want to entertain the world and are constantly innovating on how entertainment is imagined, created and delivered to a global audience. We currently stream content in more than 30 languages in 190 countries, topping over 220 million paid subscribers and are expanding into new forms of entertainment such as gaming.
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.
Realtime Data Engines | Learn More
Offers low level building blocks for the transport and processing of realtime data. For data transport we offer Kafka; for data processing we offer Flink and Mantis. Responsibilities include development of the control plane, compute resource management, reliability and availability of the data. Realtime data is critical across many business units of Netflix including Streaming, Gaming, Finance and Machine Learning platforms.
Storage and Insights | Learn More
Offers storage and insights products. Those products provide storage services to platforms, applications and users around the globe which are performant, secure and centrally managed; enabling platforms to move, store and efficiently archive data in the cloud. We offer a consistent mechanism to create & manage S3 resources, integrate Netflix ecosystem for access control and provide observability into the cost & resource lifecycle of these resources, by taking ownership of existing tools and shaping a more cohesive strategy.
Data Movement and Processing Platform | Learn More
Offers an abstracted self-service paved-paved path product to enable varied user persona across Netflix meet their low-latency Data Movement and Processing requirements; enables abstraction over complex Real-Time frameworks such as Kafka and Flink; offers a Schema driven processing experience; invests in operational automation, reliability and tools for predictable data quality.
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!
At Netflix, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and consider your specific job family, background, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.
The overall market range for roles in this area of Netflix is typically $90,000 - $900,000
This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Our culture is unique, and we tend to live by our values, so it’s worth learning more about Netflix here.
