Engineering Manager Data Platform
Blockchain intelligence company providing tools to detect, investigate, and manage crypto-related fraud, financial crime, and compliance for institutions and government agencies.
Funding history
Projects
About TRM Labs
TRM Labs provides blockchain intelligence for investigations and compliance, offering products such as forensics, wallet screening, entity screening, transaction monitoring, and APIs. It serves financial institutions, crypto businesses, and public sector agencies to trace funds, assess risk, and build cases across digital assets.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead and develop a data engineering team responsible for highly available infrastructure and services processing blockchain activity at petabyte scale. You will guide delivery, oversee reliability and performance, manage incidents, and shape data models, pipelines, clusters, and distributed systems.
Requirements
- 5+ years managing engineers
- Experience managing a team of roughly 8–15 engineers
- Technical depth in distributed systems
- Experience building and developing engineering teams
- Bachelor's degree or equivalent in Computer Science or a related field
- 5+ years of experience conceiving and implementing distributed systems from ideation through production
- Proficiency in Python
- Strong SQL or SparkSQL experience
- Experience with ClickHouse, Elasticsearch, Postgres, Redis, and Neo4j
- Experience with Airflow, DBT, Luigi, Azkaban, and Storm
- Experience with Spark, Kafka, and Flink
- Experience with Docker, Terraform, Kubernetes, and Datadog
- Ability to load, query, and transform large-scale complex datasets
Responsibilities
- Lead and develop a team of engineers
- Provide coaching and technical mentorship
- Ensure the quality and timely delivery of team work
- Oversee the availability and performance of critical services
- Drive projects against measurable outcomes and KPIs
- Establish design, usability, documentation, and knowledge-sharing practices
- Resolve operational escalations and production incidents
- Plan, estimate, and prioritize roadmap objectives
- Build reliable data services integrating with blockchains
- Engineer and optimize ETL pipelines
- Architect data models for efficient storage and retrieval
- Oversee deployment and monitoring of large-scale database clusters
- Collaborate with data scientists, backend engineers, and product managers on data models
