Key skills
PythonSQLAIMLETLData EngineeringAnalyticsSparkKafkaAirflowdbtTerraformKubernetesDockerPostgresRedisNeo4jElasticsearchDatadogBlockchainLeadershipProblem Solving
About this role
TRM Labs is a company that provides blockchain analytics and AI solutions to enhance security for law enforcement, financial institutions, and cryptocurrency businesses. As an Engineering Manager in Data Engineering, you will lead a team to develop scalable data infrastructure and services that analyze blockchain transactions, contributing to a safer financial system.
Responsibilities:
- Lead and develop a team of talented, high-impact engineers, providing cultural, technical, and hands-on leadership
- Provide regular coaching and technical mentorship to your immediate team as well as the broader engineering department
- Take direct responsibility for the quality and delivery of the team's work, and manage the end-to-end availability and performance of critical services
- Drive work based on goals and measurable outcomes that are accountable to KPIs
- Encourage best practices in design and usability, creating scalable engines with thorough documentation and knowledge sharing
- Resolve escalations arising from operations and work with various teams to solve production incidents through to resolution
- Collaborate with management and product teams to plan, estimate, and prioritize roadmap objectives and identify upcoming opportunities and risks
- Build highly reliable data services to integrate with dozens of blockchains
- Develop ETL pipelines that transform and process petabytes of structured and unstructured data in real time
- Design data models for optimal storage and retrieval to support sub-second latency for querying blockchain data
- Deploy and monitor large database clusters that are performant and highly available
- Work cross-functionally with data scientists, backend engineers and product managers to design and implement, and new data models to support TRM’s products
Requirements:
- Bachelor's degree (or equivalent) in Computer Science or a related field
- 5+ years of experience building distributed system architecture, from whiteboard to production
- Strong programming skills in Python, and SQL or SparkSQL
- Versatility. Experience across the entire spectrum of data engineering, including: Data stores (e.g., ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j), Data pipeline and workflow orchestration tools (e.g., Airflow, DBT, Luigi, Azkaban, Storm), Data processing technologies and streaming workflows (e.g., Spark, Kafka, Flink), Deployment and monitoring infrastructure in public cloud platforms (e.g., Docker, Terraform, Kubernetes, Datadog), Loading, querying, and transforming large data sets
- AI-native mindset: ability to leverage modern AI/ML tools and workflows to accelerate engineering productivity, data processing, and problem solving