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 SurfaceScout, 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 SurfaceScout 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, 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

LiveEO is a well funded startup founded in 2018 and based in Berlin. Our primary service is modelling risk to our customers’ assets and infrastructure from vegetation, ground deformation and change detection. We currently have around 160 employees from all over the world with a variety of backgrounds