Java Data Systems Engineer - High-Throughput & Low-Latency

Selby Jennings

Oakland (CA)

Hybrid

USD 120,000 - 160,000

Full time

35 hours ago
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Job summary

Selby Jennings is partnering with a technology-focused firm building systems at the intersection of financial markets and low-latency data. They seek a hands-on Java Engineer to develop high-throughput data processing systems where performance and correctness matter.

The role involves building Java components, optimizing data workflows, and collaborating with engineering and infrastructure teams in a hybrid environment with three days on-site.

Qualifications

  • 5+ years of software engineering experience.
  • Experience building backend services or data-processing systems beyond CRUD.
  • Strong knowledge of data structures, algorithms, concurrency, and system design.
  • Experience with high-throughput, multithreaded, or performance-sensitive systems.
  • Familiarity with Spring Boot, AWS/GCP, CI/CD, SQL, Python, and Unix-based environments.
  • Exposure to time-series, streaming, event-driven, or large-scale data environments.

Responsibilities

  • Build and improve Java components for high-volume data processing.
  • Transform and validate time-series and event-driven data workflows.
  • Enhance performance, reliability, observability, and test coverage.
  • Troubleshoot production issues related to latency, throughput, ordering, and data correctness.
  • Collaborate closely with engineering and infrastructure teams on production systems.

Skills

Software engineering
Backend services
Data structures
Concurrency
System design
High-throughput systems

Tools

Spring Boot
AWS/GCP
CI/CD
SQL
Python
Unix-based environments
Kafka

Job description

Selby Jennings is partnering with a technology-focused firm building systems at the intersection of financial markets and low-latency data. They seek a hands-on Java Engineer to develop high-throughput data processing systems where performance and correctness matter.

The role involves building Java components, optimizing data workflows, and collaborating with engineering and infrastructure teams in a hybrid environment with three days on-site.

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