Full-Stack Geospatial Data Engineer
You'll design everything from ingestion of raw Sentinel/Landsat scenes to the API that powers on-chain carbon registries and dashboards. You'll architect satellite-image processing pipelines and microservices that expose results via GraphQL/REST, build dashboards in Next.js/React and geospatial APIs in Node/Python/FastAPI, automate infrastructure with IaC and CI/CD, and establish engineering best practices while mentoring future engineers.
Responsibilities
- Architect end-to-end systems for satellite-image processing pipelines (STAC → xarray → Parquet/Zarr/IPFS)
- Design microservices that expose results via GraphQL/REST
- Build dashboards in Next.js/React
- Build geospatial APIs in Node/Python/FastAPI
- Automate infrastructure with IaC (Terraform/Pulumi) and CI/CD
- Implement robust orchestration using Prefect
- Profile memory and I/O to keep petabyte workflows affordable
- Establish engineering best practices and run code reviews
- Recruit and mentor the next generation of engineers
Requirements
- Fluent across the stack: Python for data and Typescript, React/Next.js, Node.js
- Data-infrastructure chops: Dask/DuckDB; S3 & object-store patterns
- Experience with data pipelining and orchestration tools like Prefect
- Experience with columnar formats (Parquet, Arrow) and chunked stores (Zarr, Cloud-Optimized GeoTIFF)
- Experience with 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: distributed systems, eventual consistency, and data-versioning at petabyte-plus scale
- Bias for action and ambiguity tolerance
- Mission-driven interest in fighting climate change
Benefits
- Remote-first, async-friendly culture with team members and hubs in Europe and USA
- Stipend for hardware, conferences, and learning