Full-Stack Geospatial Data Engineer

About the role

This position centers on developing EarthOS, an AI-powered climate and geospatial intelligence platform. The work involves transforming satellite, environmental, and asset-level data into actionable insights for various sectors. A key part of this is contributing to CYCLOPS, a natural capital and carbon MRV platform that monitors land use and carbon stocks using satellite data and geospatial analytics. The core mission is to convert vast amounts of Earth observation imagery into auditable metrics to support climate finance.

The engineer will be responsible for architecting end-to-end systems, including satellite-image processing pipelines and microservices that expose results via GraphQL/REST. This includes building dashboards using Next.js/React and geospatial APIs with Node/Python/FastAPI. The role emphasizes shipping product features that meet customer needs in climate finance.

Success in this role requires a focus on scalability and robustness. This means automating infrastructure with tools like Terraform/Pulumi, implementing continuous integration/continuous deployment, and using Prefect for orchestration. The engineer will also profile memory and I/O to ensure cost-effectiveness for petabyte-scale workflows, establish engineering best practices, conduct code reviews, and contribute to team growth.

For candidates based in the United States, the anticipated salary ranges from $40,000 to $110,000, depending on experience and location.

Skills that matter here

• Python: Used for data processing, data infrastructure, and developing geospatial APIs.
• Typescript: Required for full-stack development, particularly on the frontend with React/Next.js.
• React: Used for building user-facing dashboards and product features.
• Next.js: Leveraged for developing and deploying frontend applications and dashboards.
• Dask: Applied for handling and processing large-scale datasets efficiently within data pipelines.
• Prefect: Utilized for robust orchestration of data pipelines and workflow automation.

Who this role suits

• A person who is fluent across the full stack, from data processing to frontend development.
• Someone with strong data-infrastructure experience, including object storage and data pipelining.
• An individual with GIS and remote-sensing knowledge, comfortable with geospatial libraries and standards.
• A candidate who demonstrates systems thinking, capable of reasoning about distributed systems and petabyte-scale data.

From the employer

• Architect end-to-end systems: Design satellite-image processing pipelines (STAC → xarray → Parquet/Zarr/IPFS) and the microservices that expose results via GraphQL/REST.
• Ship product features: Build dashboards in Next.js/React and geospatial APIs in Node/Python/FastAPI that climate-finance customers love.
• Scale & harden: Automate everything with IaC (Terraform/Pulumi), CI/CD, and robust orchestration using Prefect. Profile memory & I/O to keep petabyte workflows affordable.
• Lead & mentor: Establish engineering best practices, run code reviews, and recruit the next generation of Cyclops engineers.

• Fluent across the stack: Python for data and Typescript, React/Next.js, Node.js
• Data-infrastructure chops: Dask/DuckDB; S3 & object-store patterns; Data pipelining with orchestration tools like Prefect, columnar formats (Parquet, Arrow) and chunked stores (Zarr, Cloud-Optimized GeoTIFF), Docker.
• GIS / remote-sensing know-how: Google Earth Engine, QGIS, Rasterio, GDAL, PROJ, xarray, GeoPandas, STAC, EO tiling schemes
• Cloud & DevOps: Docker, IaC, Prefect, AWS compute services and observability (Prometheus/Grafana, OpenTelemetry).
• Systems thinking: Comfortable reasoning about distributed systems, eventual consistency, and data-versioning at petabyte-plus scale.
• Bias for action & ambiguity tolerance: You turn half-written Notion docs into shipped features without hand-holding.
• Mission-driven: You want your work to fight climate change.

• For candidates based in the United States, the anticipated salary range is $40,000 - $110,000, depending on experience and location. We also welcome global candidates. For those located outside the United States, engagement structure and compensation will be tailored to your location and discussed throughout the hiring process.
• Remote-first, async-friendly culture with team members and hubs in Europe and USA
• Stipend for hardware, conferences, and learning.
• The chance to write the playbook for geospatial data in decentralized climate finance.