Full-Stack Geospatial Data Engineer

Remote $40k–$110k 1 month ago full-time quality 8.6/10

PythonTypescriptReactNext.jsNode.jsDaskDuckDBS3TerraformPulumiPrefectDocker

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.

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