Distributed Systems Engineer (L5) - Data Platform

    • Netflix, Inc.
  • Posted 60+ days ago | Updated 3 days ago

Overview

Remote
USD 100,000.00 per year
Full Time

Skills

Forms
Internet
Art
Analytics
Software deployment
Big data
Warehouse
Data warehouse
Reporting
Amazon S3
Storage
Network
Data storage
Regulatory Compliance
Caching
Redis
Memcached
Apache Cassandra
Amazon RDS
Remote Desktop Services
Elasticsearch
Streaming
ADS
Software engineering
Analytical skill
Problem solving
Leadership
Total productive maintenance
TPM
Open source
Operations support systems
Java
C++
Golang
Python
Multithreading
Management
IMPACT
Computer science
Data
HATS

Job Details

At Netflix, we want to entertain the world and are constantly innovating 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 260 million paid subscribers, and are expanding into new forms of entertainment such as gaming.

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:

Data Platform Infrastructure |Learn More

The Data Platform Infrastructure team acts as a platform for our own data platforms. Our shared infrastructure and tooling enable Netflix to innovate quickly in providing state-of-the-art data and analytics systems to the rest of the company without building bespoke scaffolding for each new system. To do this, we create high-leverage infrastructure, control, and deployment systems that are fine-tuned for running our data systems at scale.

The team plays an essential role in making it easy and efficient to use the Netflix platform and security products for building the data platform; uniquely, many of our tools and systems are written in Python, so this is a great team to consider if you enjoy working in a variety of languages.

Big Data Warehouse and Iceberg | Learn More

The Big Data Warehouse and Iceberg team is responsible for Netflix's exabyte-scale data warehouse, building and operationalizing foundational services to manage the lifecycle of core tables critical for all analytical, reporting, and data decision needs. These services enable query engines to discover tables/datasets, provide secure access to data, and efficiently store data in S3 using Iceberg table format. Additionally, the team works on efficiencies of compute, storage, and network costs, and optimality of data storage, and ensures that the data meets Netflix's standards and compliance requirements. The team is also committed to developing new features and enhancements to the Iceberg table format (which began in Netflix and is now an industry standard) and contributing to the open source.

Online Datastores | Learn More

Offers data stores as a managed service, across caching, persistence and search stores. Caching stores include Dynomite (redis), EVCache (memcached), persistence stores include Cassandra, RDS and CockroachDB and search stores include Elasticsearch and Opensearch. Responsibilities include development of data plane and control plane, reliability and availability of the data stores. Datastores directly impact critical call paths across multiple business units of Netflix including Streaming, Content, Gaming and Ads.

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:

  • 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
  • Familiarity with library development, DI frameworks (preferably SpringBoot), and container technologies




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 $100,000 - $700,000

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.
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