Senior Data Engineer — Scalable Blockchain Analytics

TRM Labs; San Francisco (CA); On-site; USD 190,000 - 220,000; Full time

Job summary

TRM Labs, based in San Francisco, seeks a Senior Data Engineer for the Data Product team. You will design and build mission-critical data services that analyze blockchain transactions at petabyte scale, enabling safer financial systems for billions of people.

You will collaborate with data scientists, backend engineers, and product managers, delivering scalable data models and pipelines while prioritizing performance, cost-efficiency, and clear communication.

Qualifications

• 5+ years of hands-on experience in architecting scalable API development, distributed system architecture
• Proven ability to design scalable data models and pipelines
• Strong Python and SQL (or SparkSQL) skills
• Experience with BigQuery and Postgres
• Ability to communicate technical decisions clearly to stakeholders

Responsibilities

• Build highly scalable data features across multiple blockchains
• Design data models for fast querying and sub-second latency
• Collaborate with data scientists, backend engineers, and product managers to implement data solutions
• Write clear design docs and share tradeoffs across teams
• Mentor engineers and analysts to raise the team's capability
• Explore AI/LLM workflows and internal tooling where relevant

Skills

Python programming

SQL / SparkSQL

Data engineering

System design

Communication

Cost-conscious design

Education

Bachelor's degree in Computer Science or related field

Tools

BigQuery

Postgres

Airflow

DBT

Dataflow

Spark

Kafka

Flink

Docker

Terraform

Kubernetes

Datadog

Job description

TRM Labs, based in San Francisco, seeks a Senior Data Engineer for the Data Product team. You will design and build mission-critical data services that analyze blockchain transactions at petabyte scale, enabling safer financial systems for billions of people.

You will collaborate with data scientists, backend engineers, and product managers, delivering scalable data models and pipelines while prioritizing performance, cost-efficiency, and clear communication.