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About the 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.
Responsibilities
- 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.
- 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.
Requirements
- 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.
- Strong SQL and PostgreSQL/PostGIS knowledge, including spatial indexes, query planning, and efficient bulk loading.
- Experience handling formats such as GeoTIFF, GeoJSON, GeoPackage, and Shapefile, with a sound understanding of coordinate reference systems, nodata, geometry validity, and the effect of resampling on data quality.
- Experience with object storage and automated pipelines, including failure recovery, deduplication, metadata validation, and reproducible outputs.
- Comfortable packaging and operating software on Linux with containers, automated tests, and useful monitoring.
- Clear communication in English and an ability to agree data contracts with scientific and application teams.
- Eligible to work in Germany.
Skills
- Python
- Go
- GDAL/Rasterio
- GeoPandas
- Shapely
- SQL
- PostgreSQL/PostGIS
- GeoTIFF
- GeoJSON
- GeoPackage
- Shapefile
- STAC/pgSTAC
- PySTAC
- TiTiler
- Martin
- OGC data services
- Apache Spark
- Dask
- xarray
- DuckDB
- Apache Arrow
- Apache Sedona
- Zarr
- NetCDF
- HDF5
- Apache Iceberg
- Temporal
- Kafka
- Kubernetes
- DIMAP
- Copernicus Sentinel-1
- Copernicus Sentinel-2
Location
- Germany
- Remote
Work Type
- Remote-first
Experience Level
- Several years of data or backend engineering experience
Benefits
- Ownership of the pipelines and data services behind a growing geospatial platform.
- Work with diverse satellite and spatial datasets, from provider deliveries to reusable analytical products.
- A Python and Go environment with room to shape processing, cataloging, and performance practices.
- 30 days of vacation
- Equipment support
- Learning support
- Close collaboration across GEOINT, platform engineering, and applied science.
About the Company
- Orcrist builds secure data intelligence software for defense, law enforcement, and enterprise teams.
- Our Sentinel platform combines data integration, AI-assisted analysis, and operational workflows.
- The GEOINT team is extending it with geospatial data services, remote-sensing capabilities, and a web-based common operational picture.