Staff Data Engineer

Overstory uses AI and advanced satellite imagery to help electric utilities identify vegetation risks, prevent outages, reduce wildfire risks, and build a more resilient grid. The Staff Data Engineer will lead the architecture and scaling of the data platform, design reliable pipelines for geospatial and temporal data, drive service-oriented and event-driven systems, and mentor engineers while establishing standards for data quality and observability.

Responsibilities:

• Architect and evolve our orchestration layer — asset graphs, quality checks, partitioning strategies, and the patterns that keep it scaling reliably
• Design and maintain production data pipelines for large-scale geospatial and temporal data, from ingestion through transformation to delivery
• Lead system design work across the data platform, including service boundaries, data contracts, and designing around the failure modes that come with each
• Drive the shift toward a service-oriented architecture, decoupling tightly bound components into services that teams can own and deploy independently
• Build event-driven workflows, replacing brittle coupling and manual coordination with durable messaging patterns
• Establish observability, testing, and data quality frameworks so problems surface before customers see them, allowing any result to be traced back and explained
• Mentor engineers and define the standards for how we build, test, and operate data systems

Requirements:

• Experience thriving at the intersection of data engineering, distributed systems, and large-scale scientific data; deeply motivated by the opportunity to reduce wildfire risk and improve grid resilience through better data patterns and infrastructure
• 10+ years of experience designing and building production-grade data pipelines and systems
• Deep hands-on experience with Dagster — asset-based orchestration, partitions, sensors, and the operational side of running it in production (comparable experience with Airflow, Prefect, or similar is a reasonable substitute if you're ready to go deep on Dagster)
• Proven track record building and operating data pipelines at scale, with a real feel for idempotency, backfills, and partitioning
• Experience in preparing systems to handle periods of high demand with a focus on testability and scalability best practices
• Strong system design skills — you can reason about boundaries, contracts, coupling, and failure modes, and explain the tradeoffs to people who'll use and build on them
• Practical experience designing service-oriented architecture, including versioning and keeping things operational through migrations
• Strong Python skills and experience with Google Cloud
• Experience with Pub/Sub and event-driven patterns
• Strong communication skills and the ability to collaborate across engineering, ML, and product
• Comfortable leading architectural discussions and mentoring other engineers
• Experience in remote-first and globally distributed team
• Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)
• We work remotely from eleven countries and are looking for candidates that are living and working in one of them: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Switzerland, Denmark and Canada
• Comfort working with geospatial data and the ways that it's stored
• Experience building data pipelines that power ML training and inference
• Experience with analytics engineering tooling and warehouse modeling in BigQuery
• Infrastructure-as-code experience and comfort owning your systems in production
• Background in remote sensing, forestry, or the utility sector