Senior Data Engineer, AI Platform — GovCloud

TRM Labs

United States

On-site

USD 140,000 - 180,000

Full time

9 days ago

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Job summary

TRM Labs is seeking a data platform engineer to own performance tuning of the StarRocks serving layer in our government cloud environment. You will build and harden data pipelines feeding investigations, ensuring reliability and fast incident response.

You will operate as a second engineer who can diagnose issues, triage production events, and use AI-assisted tools to accelerate debugging and code reviews in a highly regulated setting.

Qualifications

  • Hands-on experience operating distributed OLAP or serving-layer systems (StarRocks, Trino, ClickHouse, or similar).
  • Experience owning data pipeline reliability and incident response, using AI tools to accelerate debugging and code review.
  • Independent ownership mindset with on-call responsibility and ability to ramp quickly in production infra.

Responsibilities

  • Own performance tuning on the StarRocks serving layer, using AI-assisted profiling to fix slow query patterns before incidents.
  • Build and harden data pipelines feeding government cloud investigations with reliable changes in a compliant environment.
  • Reduce single-point-of-failure risk by becoming the second engineer who can operate and troubleshoot the serving layer.
  • Use AI-assisted debugging and log analysis to triage production issues and accelerate root-cause fixes.

Skills

Distributed OLAP systems
StarRocks
Data pipelines
Incident response
AI tooling (Claude, Cursor)
On-call readiness

Tools

StarRocks
Trino
ClickHouse

Job description

TRM Labs is seeking a data platform engineer to own performance tuning of the StarRocks serving layer in our government cloud environment. You will build and harden data pipelines feeding investigations, ensuring reliability and fast incident response.

You will operate as a second engineer who can diagnose issues, triage production events, and use AI-assisted tools to accelerate debugging and code reviews in a highly regulated setting.

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