
Data Engineer (f/m/x)
Skills
About the role
Tech stack & tools:
Core language: Python (uv-managed).
Backend services: FastAPI, Uvicorn, SQLAlchemy, Alembic and Pydantic.
Data: PostgreSQL and PostGIS (via GeoAlchemy2).
Cloud and infrastructure: AWS, mainly S3, Lambda and EC2.
Orchestration and compute: Prefect and Ray/Anyscale.
Geospatial and EO: GDAL, Rasterio, GeoPandas, Shapely, STAC (pystac) and Cloud-Optimised GeoTIFF (rio-cogeo).
ML lifecycle: MLflow.
Your challenge
Delivery & serving services
Co-own and extend the delivery-management service (SDMS) and the insight-generation and post-processing services, the path that turns model detections into delivered, customer-ready insights.
Harden these into well-tested, documented services so they are no longer a single-person dependency.
Platform, orchestration & AWS
Own and maintain the AWS and Prefect delivery platform, meaning the Lambda-based glue, the orchestration flows and the cross-repo release, and keep it deterministic and repeatable.
Manage the PostgreSQL and PostGIS data model behind delivery, including the schema and the migrations via Alembic.
Reliability & delivery operations
Be a reliable second owner for where the pipeline breaks. You unblock stuck orchestration runs, keep delivery SLAs met, and cut out manual steps.
Data quality, metadata & diagnostics
Automate QA across the serving path, covering schema and geometry integrity and coverage gaps, and maintain structured metadata and STAC entries so every delivery is traceable.
Your profile
Strong Python in production, not scripting-only.
Building and running backend services with FastAPI (or similar), SQLAlchemy, Alembic and Pydantic.
PostgreSQL, and spatial data (PostGIS, GeoAlchemy2 or equivalent) is a strong plus.
AWS in production, mainly S3, Lambda, EC2 and IAM basics.
Orchestration with Prefect, Airflow, Dagster or equivalent.
Comfort handling geospatial raster and vector data (rasterio, geopandas, shapely, STAC, COG) at a level where you can move it reliably.
Pragmatic delivery and a reliability and ops mindset, so you ship robust, well-tested services and keep them running.
Ownership and verification mindset, so you validate outputs against reality and catch results that look right but are not, using judgment and not just code.
Distributed compute with Ray or Anyscale is a plus.
MLflow, or experiment and dataset versioning is a plus.
Remote-sensing or geospatial foundations, or SAR exposure (Capella, Sentinel-1) is a plus.
Observability with structured logging, OpenTelemetry and alerting is a plus.
Satellite provider APIs such as Capella, UP42, Planet and ICEYE is a plus.
Your Benefits
The opportunity to create a product that can improve business processes and lives across the globe.
Flexible working hours and hybrid work model - we trust our employees to get their work done while maintaining a healthy work-life balance.
We empower employees to drive their own career development, take initiative and have the freedom to be creative and bold.
Not an overtime culture - we take care that overtime is done only as a necessity and always offset with time off and rest.
A collaborative and learning environment - frequent internal workshops, knowledge sharing sessions, journal clubs and hackathons.
Office located in the centre of Berlin Kreuzberg with free fruit, nuts and drinks.
Potential to participate in the employee stock option program.
Urban Sports membership and BVG subsidy, corporate pension program.
A diverse and vibrant international environment of 30+ different nationalities
About us
Questions about this role
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