Senior Distributed Systems Engineer (L5) - Remote

Bazeta

United States

Remote

USD 388.000 - 619.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Zusammenfassung

Netflix in the United States is seeking a Distributed Systems Engineer to help evolve and scale our data platform infrastructure. You will work on Spark, Trino, Druid, Iceberg and distributed databases to deliver high-performance, fault-tolerant systems across the company.

This role emphasizes collaboration with product managers, TPMs, and engineers, and offers remote work options within the U.S. The team focuses on low-latency, high-throughput data stores powering the Catalog and CDN metadata.

Qualifikationen

  • 7+ years experience crafting complex, scalable distributed data infrastructure.
  • Proficiency in Java, C++, Golang, or Python with multi-threading and memory management.
  • Experience building and operating scalable, fault-tolerant, distributed systems.
  • BS in Computer Science or related field.

Aufgaben

  • Solve real business needs at large scale by applying software engineering and analytical problem-solving skills.
  • Architect and build a robust, scalable, and highly available distributed infrastructure.
  • Lead cross-functional initiatives and collaborate with engineers, product managers, and TPMs across teams.

Kenntnisse

Java
C++
Golang
Python
Multi-threading
Memory management
Distributed systems

Ausbildung

BS in Computer Science or related field

Jobbeschreibung

Netflix in the United States is seeking a Distributed Systems Engineer to help evolve and scale our data platform infrastructure. You will work on Spark, Trino, Druid, Iceberg and distributed databases to deliver high-performance, fault-tolerant systems across the company.

This role emphasizes collaboration with product managers, TPMs, and engineers, and offers remote work options within the U.S. The team focuses on low-latency, high-throughput data stores powering the Catalog and CDN metadata.

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