SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
TRM Labs is seeking a Data Platform Engineer to join the Data Platform Serving team, working on the StarRocks-backed serving layer that powers government cloud investigations. This is a hands-on distributed systems role in one of TRM's most operationally demanding environments: a regulated, high-availability government cloud deployment.
Key responsibilities include:
- Own performance tuning on the StarRocks serving layer, using AI-assisted query profiling to identify and fix slow query patterns before they impact customers
- Build and harden data pipelines feeding government cloud investigations, leveraging AI code review workflows to ship reliable changes in a high-compliance environment
- Reduce single-point-of-failure risk by becoming the second engineer capable of independently operating and troubleshooting the serving layer, improving incident response times
- Use AI-assisted debugging and log analysis to triage production issues in a regulated environment, converting multi-hour investigations into rapid root-cause fixes
Required qualifications:
- U.S. citizenship (required for government cloud data access)
- Hands-on experience operating distributed OLAP or serving-layer systems (StarRocks, Trino, ClickHouse, or similar), including query tuning and performance optimization at scale
- Experience owning data pipeline reliability and incident response
- Comfort using AI tools (Claude, Cursor, or similar) to accelerate debugging, code review, and documentation
- Independent ownership mindset with ability to ramp quickly on unfamiliar production infrastructure and take on-call responsibility with minimal oversight
The Data Platform Serving team owns the layer that transforms TRM's data into fast, reliable answers for downstream teams and systems. The team operates with distributed async communication, evidence-based technical discussion, and decisions made close to the data. Engineers who operate the systems drive architecture decisions with input from the broader Data Platform organization.
Team cadence includes weekly syncs to review incidents and compliance milestones, async daily Slack updates on pipeline health, sprint-based planning with clear ownership, and post-incident retros. The role requires comfort with fast-moving priorities, operating under ambiguity, high personal ownership, and close cross-functional collaboration in an intense, mission-driven environment.
