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Overstory is a climate-tech company using AI and satellite imagery to help electrical utilities identify and mitigate vegetation risks to power lines, preventing outages and reducing wildfire risk. The company operates across the Americas and Europe with a globally distributed team of ~100 people.
As Staff Data Engineer, you will lead the design and scaling of Overstory's data platform—the backbone that moves enormous volumes of satellite imagery, model inferences, and utility network data through orchestrated pipelines to support customer decision-making and AI model training. You will own the architecture of this platform and set the direction for its evolution.
Key responsibilities include:
- Architect and evolve the orchestration layer (asset graphs, quality checks, partitioning strategies) to maintain reliable scaling
- 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 failure-mode analysis
- Drive the shift toward service-oriented architecture, decoupling tightly bound components into independently deployable services
- Build event-driven workflows using durable messaging patterns to replace brittle coupling
- Establish observability, testing, and data quality frameworks so issues surface before customers encounter them
- Mentor engineers and define standards for building, testing, and operating data systems
You will collaborate closely with data, ML, and product engineers, as well as product teams, to balance pragmatic delivery with durability, traceability, and scalability. As a senior technical leader, you'll drive architectural decisions and mentor other engineers.
Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST).
REQUIREMENTS:
- 10+ years of experience designing and building production-grade data pipelines and systems
- Deep hands-on experience with Dagster (asset-based orchestration, partitions, sensors, production operations); comparable experience with Airflow or Prefect acceptable if ready to go deep on Dagster
- Proven track record building and operating data pipelines at scale with real understanding of idempotency, backfills, and partitioning
- Strong system design skills: ability to reason about boundaries, contracts, coupling, and failure modes
- Practical experience designing service-oriented architecture, including versioning and operational migrations
- Strong Python skills and experience with Google Cloud
- Experience with Pub/Sub and event-driven patterns
- Strong communication skills and ability to collaborate across engineering, ML, and product
- Comfortable leading architectural discussions and mentoring engineers
- Experience in remote-first and globally distributed teams
- Experience preparing systems for high-demand periods with focus on testability and scalability
NICE TO HAVE:
- Comfort with geospatial data and storage patterns
- Experience building data pipelines for ML training and inference
- Analytics engineering tooling and warehouse modeling in BigQuery
- Infrastructure-as-code experience and comfort owning systems in production
- Background in remote sensing, forestry, or utility sector
