Senior Data Engineer, Graph Analytics

Company: TRM Labs

Location: Location not specified (Remote)

Type: Full-time

Level: Senior

Remote: Yes

Posted: 2026-02-22

About this role

Build a Safer World.


TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all.


As a Senior Data Engineer on the Graph Analytics team, you will build scalable graph systems that analyze large networks of cryptocurrency transactions. You will collaborate closely with engineers, data scientists, and investigators to design mission-critical graph algorithms that analyze flows of funds. You will leverage distributed databases and graph processors to implement real-time graph algorithms at the multi-blockchain scale. You will collaborate with data science teams to identify opportunities to apply tools and techniques from graph theory to a variety of predictive learning problems.


The impact you will have:

  • Designing and implementing graph algorithms that analyze large cryptocurrency transaction networks at multi-blockchain scale
  • Researching new graph-native technology to evaluate benefit to data science and data engineering teams at TRM
  • Working on a highly cross-functional team that collaborates with cryptocurrency investigators to identify key user stories and requirements for new graph algorithms and features
  • Understanding and refining TRM’s risk models which analyze large networks of cryptocurrency transactions to assign risk scores to addresses
  • Communicating complex implementation details to a variety of audiences from investigators and customer success stakeholders to data engineers and data scientists
  • Integrating with a diverse set of data ...

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