Data Engineer; f​/m​/x

Build the Market Leader in Satellite Analytics with us at LiveEO

We are looking for a Data Engineer (f/m/x) to own and harden the data-delivery and serving backbone of Surface Scout, LiveEO's solution for monitoring changes around critical assets like pipelines and power grids to protect utility customers from third-party interference. You will make the path from detection to delivered customer insight reliable and repeatable. This covers the delivery-management and insight-generation services, the post-processing steps, and the AWS and Prefect platform that runs them end to end, at scale across thousands of km at a daily cadence.

While our remote-sensing and detection-model specialists focus on imagery and models, you will be the custodian of the systems that turn their output into a dependable product that is deterministic, observable and resilient. This is a hands-on, delivery-first backend and platform role, with plenty of room to grow into the wider geospatial data platform.

You will sit within the Surface Scout Data Engineering & ML squad and work alongside the senior engineers who own the delivery and serving platform, sharing that ownership so the systems are no longer a single-person dependency. You will collaborate with the App squad and the platform teams that co-own the shared Imagery API, and partner with our in-house labelling studio, Operations Support Studio (OST), on data quality.

SAR change-detection research, meaning coherent change detection, InSAR and semantic-change work, is driven by our remote-sensing specialist together with LiveEO's Section 4 team. You consume its outputs, you do not build them.

Tech stack & tools:

• Core language:
  Python (uv-managed).

• Backend services:
  FastAPI, Uvicorn, SQL Alchemy, 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, Geo Pandas, Shapely, STAC (pystac) and Cloud-Optimised GeoTIFF (rio-cogeo).

• ML lifecycle: MLflow.

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.

• Strong Python in production, not scripting-only.

• Building and running backend services with FastAPI (or similar), SQL Alchemy, 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 aplus.

• 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, Open Telemetry and alerting is a plus.

• Satellite provider APIs such as Capella, UP42, Planet and ICEYE is a plus.

• 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…