About the Role

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.

Why this Role is Unique

Own the product & the pipeline: You’ll design everything from ingestion of raw Sentinel/Landsat scenes to the API that powers on-chain carbon registries and dashboards.
Impact at scale: Each line of code helps move millions of tonnes of CO₂ equivalent through verifiable nature-based projects.
Novel technology: No legacy cruft. Pick the right datastores, cloud primitives, and CI/CD flows from day one.
Educational environment: You will work with professors and academics who are top of their fields so you understand the why, while doing the how.
Path to leadership: You’ll play a role in hiring and mentoring subsequent engineers, setting technical direction for years to come.

What You'll Do

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.

What You'll Need

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.

Extra Credit

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.

What We Offer

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.

How to Apply

Email careers@dclimate.net with:

“CYCLOPS - Geospatial Wizard” in the subject line.
Your resume and GitHub / portfolio links.
A short note (<300 words) describing the most complex data pipeline you’ve built and what you’d do differently next time.

We review every application personally. If you’re excited by satellites, big data, and real-world impact, let’s talk.

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