Engineering Manager, Data Engineering
New
T
TRM LabsData Infrastructure / AI
United StatesFull-TimeManager
Salary220,000 - 240,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- DockerPythonSQLETLKubernetesData engineeringData modelingDistributed Systems
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.
- Experience with data stores (e.g., ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j).
- Experience with data pipeline and workflow orchestration tools (e.g., Airflow, DBT, Luigi, Azkaban, Storm).
- Experience with data processing technologies and streaming workflows (e.g., Spark, Kafka, Flink).
- Experience with deployment and monitoring infrastructure in public cloud platforms (e.g., Docker, Terraform, Kubernetes, Datadog).
- Ability to load, query, and transform large data sets.
- AI-native mindset: ability to leverage modern AI/ML tools and workflows.
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.
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