Overstory - Staff Data Engineer
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) • Dagster • Proven track record building and operating data pipelines at scale, with a real feel for idempotency, backfills, and partitioning • data pipelines • 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 • system design • Practical experience designing service-oriented architecture, including versioning and keeping things operational through migrations • service-oriented architecture • Strong Python skills and experience with Google Cloud • Python • Google Cloud • Experience with Pub/Sub and event-driven patterns • Pub/Sub • 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 • 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 • Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description. • Note:
Responsibilities
• In collaboration with data, ML, and product colleagues, you will: • 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.
Benefits
• Competitive, location-specific compensation and benefits • Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around • A company culture that genuinely embodies each of our core values • To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis
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