Full-Stack Geospatial Data Engineer
About The Position
dClimate Labs is building EarthOS, an AI-powered climate and geospatial intelligence platform that turns satellite, environmental, and asset-level data into actionable insights for companies, investors, and insurers. CYCLOPS is dClimate Labs’ natural capital and carbon MRV platform. It helps carbon project developers, investors, buyers, and agricultural companies monitor land cover, vegetation health, carbon stocks, land-use change, and project risks using satellite data and geospatial analytics. Our mission is to turn petabytes of Earth observation imagery into auditable metrics of carbon stocks, vegetation health, and land use change so that climate finance can flow where it matters. We’re looking for a hands-on full-stack data engineer to advance CYCLOPS across the full stack, from APIs 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 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.
Nice To Haves
- Experience leading a small team or owning a large production system.
- GPU accelerated image processing (cuDF, RAPIDS, TorchGeo).
- Machine Learning knowledge and MLOps (PyTorch/TensorFlow)
- Experience with carbon/MRV methodologies or environmental/agricultural science.
Responsibilities
- 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.
Benefits
- Stipend for hardware, conferences, and learning.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
