Full-Stack Geospatial Data Engineer
We are looking for a hands-on full-stack data engineer to advance reputed company across the full stack, from reputed company and geospatial data pipelines to frontend tools used by carbon project developers, investors, buyers, and agricultural companies.
Requirements
- 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 reputed company, columnar formats (Parquet, reputed company) and chunked stores (Zarr, reputed company-Optimized GeoTIFF), reputed company
- GIS / remote-sensing know-how: reputed company reputed company reputed company, QGIS, Rasterio, GDAL, reputed company, xarray, GeoPandas, STAC, EO tiling schemes
- reputed company & DevOps: reputed company, IaC, reputed company, AWS compute services and observability (reputed company/Grafana, OpenTelemetry)
- Systems thinking: Comfortable reasoning about distributed systems, reputed company consistency, and data-versioning at petabyte-plus reputed company
- Bias for reputed company & ambiguity tolerance: You turn half-written reputed company docs into shipped features without hand-holding
- Mission-driven: You want your work to fight climate change
Benefits
- 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 reputed company for geospatial data in decentralized climate finance
Originally posted on Himalayas
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