Geospatial Data Engineer
Builds the data foundation for Orcrist's geospatial intelligence platform: developing Python and Go pipelines to ingest, process, catalog, and serve satellite imagery and vector geodata using GDAL, PostGIS, STAC, and S3-compatible storage. Remote-first within Germany, serving defense, law enforcement, and enterprise customers.
- Compensation
- Not disclosed
- Location
- Remote
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Several years of data or backend engineering experience with substantial hands-on geospatial or Earth observation data work
- Strong Python skills
- Practical Go experience for services, integrations, or processing infrastructure
- Experience with GDAL/Rasterio and vector tooling such as GeoPandas or Shapely
- Strong SQL and PostgreSQL/PostGIS knowledge, including spatial indexes, query planning, and bulk loading
- Experience with GeoTIFF, GeoJSON, GeoPackage, Shapefile formats and coordinate reference systems, nodata, geometry validity, resampling effects
- Experience with object storage and automated pipelines, including failure recovery, deduplication, metadata validation
- Comfortable packaging and operating software on Linux with containers, automated tests, and monitoring
- Clear communication in English
- Eligible to work in Germany
Nice to have
- STAC/pgSTAC, PySTAC, TiTiler, Martin, or OGC data services
- Apache Spark, Dask, xarray, DuckDB, Apache Arrow, or Apache Sedona; familiarity with Zarr, NetCDF, HDF5
- Apache Iceberg or similar analytical table formats
- Temporal, Kafka, Kubernetes, and self-hosted or air-gapped operations
- Provider delivery formats such as DIMAP or satellite acquisition APIs
- Experience handling Copernicus Sentinel-1 and Sentinel-2 data
- Experience supporting scientific processing in production environments
- Experience working in defence and intelligence environments
- Practical ability in agentic software development using coding agents
- German language skills or contributions to geospatial open source
Full description
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.