Geospatial Data Engineer

Orcrist is building a next generation data intelligence platform using cutting-edge technologies. We're handling petabyte-scale data with sub-second queries. Our product is a Kubernetes‑based platform delivered as B2B SaaS or as a self‑hosted on‑prem solution, including air‑gapped deployments. We enable customers across defense, law enforcement, and enterprise to turn mission-critical data into actionable intelligence.

Role

Build the data foundation that makes satellite imagery and geospatial datasets discoverable, reliable, and ready for analysis. You'll use Python and Go to develop ingestion, processing, cataloging, and serving capabilities for data we acquire, retain, and use within our platform.

The work spans provider APIs, large raster deliveries, vector datasets, spatial databases, and object storage. You'll partner with Foundation and Platform engineers on infrastructure, and with data scientists and application engineers on the data products they need.

What you'll do

• Build provider integrations for imagery search, acquisition, download, and delivery tracking, handling authentication, rate limits, retries, and differences in vendor metadata.
• Ingest optical, multispectral, thermal, and SAR products from commercial and open sources. Our intended provider landscape includes Airbus Pléiades, Satellogic, SatVu, ICEYE, and Copernicus Sentinel missions.
• Develop raster ETL for metadata extraction, coordinate transformation, reprojection, resampling, mosaicking, COG creation, overviews, and quality checks.
• Build vector pipelines for geometry validation, schema normalization, spatial partitioning, indexing, and production of GeoParquet and PMTiles assets.
• Implement imagery cataloging with STAC/pgSTAC and spatial data services with PostGIS, preserving acquisition times, footprints, source metadata, processing history, and access restrictions.
• Design efficient storage and delivery paths using S3-compatible buckets, HTTP range requests, columnar formats, and appropriate caching and tiling strategies.
• Integrate processing with Sentinel's orchestration and service contracts. Make workflows resumable, safe to retry, observable, and capable of processing data larger than memory.
• Track freshness, completeness, lineage, and processing cost. Diagnose malformed deliveries, missing assets, inconsistent catalogs, and performance bottlenecks.

About you

• Several years of data or backend engineering experience, with substantial hands-on work on geospatial or Earth observation data.
• Strong Python skills and practical Go experience for services, integrations, or processing infrastructure.
• Experience with GDAL/Rasterio and vector tooling such as GeoPandas, Shapely, or equivalent libraries.