Staff Data Engineer
New
O
OverstoryGeospatial analytics
Location: United States; Secondary Locations: Sweden, Canada, Ireland, France, Portugal, United Kingdom, Netherlands, Denmark, Switzerland; Workplace: Remote, Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)Full-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 10+ years of experience designing and building production-grade data pipelines and systems
- Required Skills
- PythonGCPDistributed Systems
Requirements
- Bring 10+ years of experience designing and building production-grade data pipelines and systems.
- Have hands-on Dagster experience, including asset-based orchestration, partitions, sensors, and production operations; Airflow, Prefect, or similar experience is an acceptable substitute.
- Have a track record building and operating data pipelines at scale, including idempotency, backfills, and partitioning.
- Have experience preparing systems for periods of high demand, with attention to testability and scalability.
- Demonstrate strong system design skills, including reasoning about boundaries, contracts, coupling, and failure modes.
- Have practical experience designing service-oriented architecture, including versioning and migrations.
- Bring strong Python skills and experience with Google Cloud.
- Have experience with Pub/Sub and event-driven patterns.
- Collaborate across engineering, ML, and product, and be comfortable leading architectural discussions and mentoring engineers.
- Geospatial data, ML training and inference pipelines, BigQuery, infrastructure as code, remote sensing, forestry, or utility-sector experience are nice to have.
Responsibilities
- Architect and evolve the orchestration layer, including asset graphs, quality checks, and partitioning strategies.
- Design and maintain production data pipelines for large-scale geospatial and temporal data, from ingestion through delivery.
- Lead data platform system design, including service boundaries, data contracts, and failure modes.
- Drive the transition to service-oriented architecture by decoupling components into independently owned and deployed services.
- Build event-driven workflows using durable messaging patterns.
- Establish observability, testing, and data quality frameworks that make results traceable.
- Mentor engineers and define standards for building, testing, and operating data systems.
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