[Hiring] Staff Data Engineer @Overstory

Role Description

As a Staff Data Engineer at Overstory, you will lead the design and scaling of the data platform that enables Overstory’s AI-powered vegetation analysis. Your responsibilities include:

• Owning the architecture of the data platform and setting the direction for its evolution.
• Working closely with data, ML, and product engineers to ensure data flow balances pragmatic delivery with durability, traceability, and scalability.
• Mentoring other engineers and driving architectural decisions.
• Setting standards for pipeline design, service boundaries, and data quality across Overstory.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do

In collaboration with data, ML, and product colleagues, you will:

• Architect and evolve our orchestration layer — asset graphs, quality checks, partitioning strategies, and scaling patterns.
• 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 and data contracts.
• Drive the shift toward a service-oriented architecture, decoupling tightly bound components into independently deployable services.
• Build event-driven workflows, replacing brittle coupling and manual coordination with durable messaging patterns.
• Establish observability, testing, and data quality frameworks to surface problems before customers see them.
• Mentor engineers and define standards for building, testing, and operating data systems.

Qualifications

• Experience thriving at the intersection of data engineering, distributed systems, and large-scale scientific data.
• 10+ years of experience designing and building production-grade data pipelines and systems.
• Deep hands-on experience with Dagster or comparable orchestration tools.
• Proven track record building and operating data pipelines at scale.
• Experience preparing systems for high demand with a focus on testability and scalability.
• Strong system design skills, including reasoning about boundaries, contracts, coupling, and failure modes.
• Practical experience designing service-oriented architecture.
• Strong Python skills and experience with Google Cloud.
• Experience with Pub/Sub and event-driven patterns.
• Strong communication skills and ability to collaborate across teams.
• Comfortable leading architectural discussions and mentoring other engineers.
• Experience in remote-first and globally distributed teams.

Nice To Have

• Comfort working with geospatial data.
• Experience building data pipelines that power ML training and inference.
• Experience with analytics engineering tooling and warehouse modeling in BigQuery.
• Infrastructure-as-code experience.
• Background in remote sensing, forestry, or the utility sector.

What We Offer

• Competitive, location-specific compensation and benefits.
• Flexible, autonomous, and collaborative working environment rooted in trust.
• Home office stipend, coworking, and ongoing education budgets.
• A company culture that embodies core values.
• Mission-driven work that reduces wildfires and helps solve the climate crisis.

About Our Team

We are a fast-growing team of about 100 people from all over the world, representing fifteen nationalities and speaking fourteen languages. We work remotely from eleven countries and gather once a year for an in-person team event.

Diversity & Inclusion

We value diversity and believe that the best ideas emerge when people with different backgrounds work together. We are committed to creating an equitable and inclusive culture.

Our Values

• Tackling the climate crisis is our greatest mission.
• We act with urgency.
• Our curiosity fuels our growth.
• We’re rooted in diversity.
• We care for each other.
• Trust is fundamental.

Use of AI in Our Hiring Process

We sometimes use AI tools to support parts of our hiring process, ensuring job descriptions are clear and inclusive. All hiring decisions are made by people, not machines.