Distributed Systems Engineer L5, Data Platform

Netflix

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$388,000–$619,000 / yr
Posted
10 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k
This role $504k
$76k most similar roles pay here $677k

This role pays more than 99% of similar roles. Most pay $147,325–$214,000 — the shaded band above. At the midpoint, this role pays about $504k versus about $181k for comparable roles.

Based on 240 similar postings.

Employer

About Netflix

Netflix is the world''s leading streaming entertainment service, offering a vast library of TV series, films, documentaries, and original content to subscribers in over 190 countries. Industry: Streaming Entertainment & Media

Netflix currently has 28 open roles on FindRole.

Listed pay typically runs $440,000–$750,000 across 27 roles with salary data.

Most-posted roles

View all roles at Netflix

At a glance

TL;DR · Distributed Systems Engineer L5, Data Platform

Distributed Systems Engineer (L5) - Data Platform is a role within the Data Platform Organization focused on building high-performance infrastructure for large-scale data processing and storage. You will work on the Big Data Compute team to provide cloud-native platforms for Spark-based ETL processes into an exabytes-scale warehouse, or join the Online DataStores team to develop low-latency, high-throughput in-memory and distributed caching solutions for mission-critical services like streaming catalogs and CDN metadata. The role involves building features, performance enhancements, and robust distributed infrastructure while collaborating with open source communities. Required technical skills include proficiency in Java, C++, Golang, or Python, along with experience in Spark, Presto, Trino, Druid, and Iceberg. You will solve complex problems regarding data at scale, ensuring systems are reliable, cost-efficient, and highly available for various business functions like machine learning and analytics.

What you'll do

  • Build and maintain high-performance, reliable, and cost-efficient distributed data storage solutions at scale.
  • Develop cloud-native platforms for distributed data processing using Spark and other big data technologies.
  • Engineer low-latency, high-throughput in-memory and distributed data storage systems for mission-critical services.
  • Create secure and intuitive abstraction layers to improve developer productivity on base storage systems.
  • Architect and build robust, scalable, and highly available distributed infrastructure.
  • Implement performance enhancements and new features for large-scale analytics and ETL processes.
  • Contribute to and shape open-source projects within the data community.
  • Solve complex technical problems related to managing exabytes of data across various business functions.

What we're looking for

  • Bachelor of Science in Computer Science or a related field.
  • 7+ years of experience crafting complex, scalable distributed data infrastructure.
  • Proficiency in Java, C++, Golang, or Python.
  • 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.
  • Experience with Spark, Presto/Trino, Druid, Iceberg, and distributed database systems.

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