Staff Data Engineer

Role overview A staff-level data engineering role focused on architecting the data platform behind an AI-powered vegetation and grid resilience product. The position involves large-scale geospatial and temporal data pipelines, orchestration, and service-oriented architecture for ML-driven analytics. It is a senior technical leadership role that sets standards, drives architecture, and mentors engineers across data, ML, and product teams. Candidates must be located in Europe or Eastern North America.

Responsibilities - Architect and evolve the orchestration layer, including asset graphs, partitioning, quality checks, and scalable patterns. - Design and maintain production pipelines that move large geospatial and temporal datasets from ingestion through delivery. - Lead system design across the data platform, defining service boundaries, data contracts, and failure-mode handling. - Drive the move toward service-oriented architecture, decoupling components so teams can own and deploy services independently. - Build event-driven workflows that replace brittle coupling with durable messaging patterns. - Establish observability, testing, and data quality frameworks so issues surface before reaching customers.

Requirements - 10+ years building production-grade data pipelines and systems at scale. - Deep hands-on experience with Dagster, including asset-based orchestration, partitions, and sensors in production; comparable Airflow or Prefect experience is acceptable. - Strong foundation in distributed systems, idempotency, backfills, and large-scale scientific data. - Proven ability to lead architectural discussions and mentor other engineers. - Strong communication skills and experience collaborating across engineering, ML, and product functions. - Comfort working in a remote-first, globally distributed team.

Nice to have - Experience with geospatial data formats and storage approaches. - Background building data pipelines that power ML training and inference workloads. - Familiarity with BigQuery, analytics engineering tooling, and warehouse modeling. - Infrastructure-as-code experience and comfort owning systems in production. - Domain background in remote sensing, forestry, or the utility sector.

Benefits and work setup - Remote position with flexible, autonomy-driven work culture rooted in trust. - Competitive, location-specific compensation and benefits. - Home office stipend, coworking budget, and ongoing education allowance. - Annual in-person team gathering plus optional regional meetups. - Mission-driven work focused on wildfire risk reduction and grid resilience.