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Distributed Systems Engineer - Data Platform

$388k
Full-time

Netflix

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 Organization enables 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 Team Currently Hiring:

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.
We provide extremely low-latency yet high-throughput in-memory and distributed data storage solutions across the company. Our services power mission-critical Tier-0 Netflix services such as the streaming Catalog and Content Delivery Network (CDN) metadata. We are looking for passionate and innovative software engineers to join our team to build novel caching architectures that push the limits of performance, cost efficiency, utility, and usability.

This would be your dream job if you enjoy:

  • Solving real business needs at a 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:

  • 7+ years experience in crafting complex, scalable distributed data infrastructure

  • Proficiency in Java, C++, Golang, or Python with a solid understanding of multi-threading and memory management

  • Proven track record of developing and maintaining high-impact systems

  • Experience building and operating scalable, fault-tolerant, distributed systems

  • You have a BS in Computer Science or a related field

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $388,000.00 - $619,000.00. This compensation range will vary based on location.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here .

Netflix is a unique culture and environment. Learn more here .

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.

Vacancy posted 9 days ago
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