Geospatial Data Engineer

Orcrist builds the Orcrist Intelligence Platform (OIP), a secure, Kubernetes-native system delivering geospatial intelligence worldwide. Deployments run as SaaS and self-hosted/on‑prem (air‑gapped).

Build and operate data pipelines that supply GEOINT services with accurate, compliant, and performant spatial data. Own ingestion, transformation, versioning, and distribution across cloud and air‑gapped environments. Collaborate with Data Analytics Team in creating value‑adding data products.

• Develop ingestion pipelines using Python, GDAL, Rasterio, tippecanoe, and PostGIS for vector/raster/3D datasets
• Automate tiling, generalization, and 3D tile generation (Cesium 3D Tiles, quantized mesh, terrain) with incremental update workflows
• Implement data quality checks (topology validation, completeness, coordinate reference integrity) and provenance tracking (lineage metadata, checksums)
• Manage storage lifecycle across cloud (S3/GCS) and on‑prem object stores; optimize performance and cost
• Package data for offline distribution (MBTiles, geopackages, zipped 3D tiles), including delta updates and secure transfer
• Collaborate with Data Acquisition and Licensing to enforce usage rights, export control, and compliance
• Monitor pipelines (Prometheus, Grafana), maintain runbooks, and participate in on‑call/incident response
• Own end‑to‑end sourcing of new geospatial datasets (commercial and freely available)

• 5+ years geospatial data engineering with large datasets and production ownership
• Delivered pipelines supporting map services, analytics, or offline distribution
• Worked under licensing/export constraints and documented compliance evidence
• Participated in on‑call/incident response for data platforms
• German language (B1+) and knowledge of European geospatial data providers (Copernicus, HERE, Airbus, Maxar)
• Experience with geospatial data engineering in a defence and intelligence environment
• Experience with vector tile optimizations, level‑of‑detail algorithms, or GPU‑accelerated processing (cu Spatial)
• Familiarity with NiFi, Kafka, or streaming pipelines for geospatial events
• Contributions to open‑source geospatial tools or data pipelines

• Build the spatial data backbone powering Orcrist’s missions
• Work with modern geospatial stack: GDAL, tippecanoe, PostGIS, Maplibre GL JS/Deck.gl, Argo, Kubernetes. Bring your own ideas forward in modernising frameworks and tools
• Remote‑first Germany, equipment and learning budgets, mission‑driven impact
• Collaborate with data acquisition, product, and forward‑deployed teams on real‑world challenges