Staff Data Engineer

<div class=&quot;content-intro&quot;><p>The climate crisis is the defining challenge of our time—but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting-edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes.</p> <p>The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change.&nbsp;</p> <p>One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines.&nbsp;</p> <p>That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid.</p> <p>Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good.</p> <p>Join us to help us build a more resilient world together.&nbsp;</p></div><h2>Role &amp; Team</h2> <p>As a <strong>Staff Data Engineer</strong> at Overstory, you will lead the design and scaling of the data platform that enables Overstory’s AI-powered vegetation analysis. Our analysis depends on moving enormous volumes of satellite imagery, model inferences, and utility network data through orchestrated pipelines reliably, repeatably, and on time to support customer decision-making. You&#39;ll own the architecture of that platform and set the direction for how it evolves.</p> <p>You&#39;ll work closely with data, ML, and product engineers, as well as product teams, to make sure the data flowing into our models and out to our customers balances pragmatic delivery with durability, traceability, and scalability. As a senior technical leader, you&#39;ll mentor other engineers, drive architectural decisions, and set standards for pipeline design, service boundaries, and data quality across Overstory.</p> <p><strong>Time zone requirement: </strong>Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)</p> <h2><strong>What You&#39;ll Do</strong></h2> <p>In collaboration with data, ML, and product colleagues, you will:</p> <ul> <li>Architect and evolve our orchestration layer — asset graphs, quality checks, partitioning strategies, and the patterns that keep it scaling reliably.</li> <li>Design and maintain production data pipelines for large-scale geospatial and temporal data, from ingestion through transformation to delivery.</li> <li>Lead system design work across the data platform, including service boundaries, data contracts, and designing around the failure modes that come with each.</li> <li>Drive the shift toward a service-oriented architecture, decoupling tightly bound components into services that teams can own and deploy independently.</li> <li>Build event-driven workflows, replacing brittle coupling and manual coordination with durable messaging patterns.</li> <li>Establish observability, testing, and data quality frameworks so problems surface before customers see them, allowing any result to be traced back and explained.</li> <li>Mentor engineers and define the standards for how we build, test, and operate data systems.</li> </ul> <h2><strong>Skills &amp; Experience</strong></h2> <ul> <li>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</li> <li>10+ years of experience designing and building production-grade data pipelines and systems</li> <li>Deep hands-on experience with <strong>Dagster</strong> — 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&#39;re ready to go deep on Dagster)</li> <li>Proven track record building and operating <strong>data pipelines</strong> at scale, with a real feel for idempotency, backfills, and partitioning</li> <li>Experience in preparing systems to handle periods of high demand with a focus on testability and scalability best practices</li> <li>Strong <strong>system design</strong> skills — you can reason about boundaries, contracts, coupling, and failure modes, and explain the tradeoffs to people who&#39;ll use and build on them</li> <li>Practical experience designing <strong>service-oriented architecture</strong>, including versioning and keeping things operational through migrations</li> <li>Strong <strong>Python</strong> skills and experience with <strong>Google Cloud</strong></li> <li>Experience with <strong>Pub/Sub</strong> and event-driven patterns</li> <li>Strong communication skills and the ability to collaborate across engineering, ML, and product</li> <li>Comfortable leading architectural discussions and mentoring other engineers</li> <li>Experience in remote-first and globally distributed team</li> </ul> <h2><strong>Nice To Have</strong></h2> <ul> <li>Comfort working with geospatial data and the ways that it’s stored</li> <li>Experience building data pipelines that power ML training and inference</li> <li>Experience with analytics engineering tooling and warehouse modeling in BigQuery</li> <li>Infrastructure-as-code experience and comfort owning your systems in production</li> <li>Background in …