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Overstory

Vegetation risk analytics for utilities

Staff Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 10 years of experience designing and building production-grade data pipelines and systems.
  • Hands-on experience with Dagster, including asset-based orchestration, partitions, sensors, and production operations; comparable experience with Airflow, Prefect, or similar is an acceptable substitute if prepared to develop deep Dagster expertise.
  • Experience building and operating data pipelines at scale, including idempotency, backfills, and partitioning.
  • Experience preparing systems to handle periods of high demand, with a focus on testability and scalability best practices.
  • Strong system design skills, including reasoning about boundaries, contracts, coupling, failure modes, and tradeoffs.
  • Practical experience designing service-oriented architecture, including versioning and maintaining operations through migrations.
  • Strong Python skills and experience with Google Cloud.
  • Experience with Pub/Sub and event-driven patterns.
  • Experience at the intersection of data engineering, distributed systems, and large-scale scientific data.
  • Ability to collaborate across engineering, machine learning, and product teams.
  • Comfort leading architectural discussions and mentoring other engineers.
  • Experience working in a remote-first and globally distributed team.

Responsibilities

  • Architect and evolve the orchestration layer, including asset graphs, quality checks, partitioning strategies, and scalable operating patterns.
  • Design and maintain production data pipelines for large-scale geospatial and temporal data, from ingestion through transformation to delivery.
  • Lead system design across the data platform, including service boundaries, data contracts, and failure-mode-aware design.
  • Drive the shift toward a service-oriented architecture by decoupling tightly bound components into services that teams can own and deploy independently.
  • Build event-driven workflows that replace brittle coupling and manual coordination with durable messaging patterns.
  • Establish observability, testing, and data quality frameworks so issues surface before customers see them and results can be traced and explained.
  • Mentor engineers and define standards for building, testing, and operating data systems.

Desired Qualifications

  • Comfort working with geospatial data and how it is stored.
  • Experience building data pipelines that power machine learning training and inference.
  • Experience with analytics engineering tooling and warehouse modeling in BigQuery.
  • Infrastructure-as-code experience and comfort owning systems in production.
  • Background in remote sensing, forestry, or the utility sector.

About the Company

Overstory

Vegetation risk analytics for utilities

Overstory provides vegetation intelligence for utility companies by analyzing high-resolution satellite imagery with machine learning to monitor vegetation growth near power lines. The platform maps vegetation proximity, flags high-risk areas, and delivers prioritized actions and customizable alerts to support vegetation management. It differentiates itself by specializing in the electric utility sector, offering frequent imagery and ML-based risk scoring through a scalable subscription service for utilities of all sizes. The goal is to help utilities prevent power outages and wildfires with data-driven, actionable insights for proactive vegetation management.

Company size
51-200
Company stage
Series B
Total funding
$67.9M
Headquarters
Amsterdam, Netherlands
Founded
2018

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