Staff Data Engineer
Overstory
Role & Team
As a Staff Data Engineerat 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'll own the architecture of that platform and set the direction for how it evolves. You'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'll mentor other engineers, drive architectural decisions, and set 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 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.
Skills & Experience
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)
Proven track record building and operating
data pipelines
at scale, with a real feel for idempotency, backfills, and partitioning
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
Practical experience designing
service-oriented architecture
, including versioning and keeping things operational through migrations
Strong
Python
skills and experience with
Google Cloud
Experience with
Pub/Sub
and event-driven patterns
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
Nice To Have
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. What We Offer
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
Home office stipend, coworking and ongoing education budgets
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
As a Staff Data Engineerat 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'll own the architecture of that platform and set the direction for how it evolves. You'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'll mentor other engineers, drive architectural decisions, and set 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 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.
Skills & Experience
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)
Proven track record building and operating
data pipelines
at scale, with a real feel for idempotency, backfills, and partitioning
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
Practical experience designing
service-oriented architecture
, including versioning and keeping things operational through migrations
Strong
Python
skills and experience with
Google Cloud
Experience with
Pub/Sub
and event-driven patterns
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
Nice To Have
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. What We Offer
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
Home office stipend, coworking and ongoing education budgets
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
Reference: WJCPA-4214_4656442 · Posted 13 Nov 2026, 04:37 PM