LiveEO is seeking a Data Engineer to own and harden the data-delivery and serving backbone of SurfaceScout, LiveEO's solution for monitoring critical assets such as pipelines and power grids. You will ensure the path from detection to delivered customer insight is reliable, observable, and scalable. This hands-on backend and platform role focuses on delivery-management, post-processing, and running the AWS and Prefect-based platform end-to-end, at scale across thousands of kilometres daily. You will sit within the SurfaceScout Data Engineering & ML squad and collaborate with the App squad and platform teams that co-own the shared Imagery API, while partnering with our in-house Operations Support Studio (OST) on data quality. SAR change-detection research is driven by remote-sensing specialists, and you will consume outputs rather than build them.
LiveEO is seeking a Data Engineer to own and harden the data-delivery and serving backbone of SurfaceScout, LiveEO's solution for monitoring critical assets such as pipelines and power grids. You will ensure the path from detection to delivered customer insight is reliable, observable, and scalable. This hands-on backend and platform role focuses on delivery-management, post-processing, and running the AWS and Prefect-based platform end-to-end, at scale across thousands of kilometres daily. You will sit within the SurfaceScout Data Engineering & ML squad and collaborate with the App squad and platform teams that co-own the shared Imagery API, while partnering with our in-house Operations Support Studio (OST) on data quality. SAR change-detection research is driven by remote-sensing specialists, and you will consume outputs rather than build them.
Technical stack and responsibilities: - Core language: Python (uv-managed). - Backend services: FastAPI, Uvicorn, SQLAlchemy, Alembic, Pydantic. - Data: PostgreSQL and PostGIS (via GeoAlchemy2). - Cloud: AWS (S3, Lambda, EC2, IAM basics). - Orchestration: Prefect and Ray/Anyscale. - Geospatial: GDAL, Rasterio, GeoPandas, Shapely, STAC (pystac), and COG (rio-cogeo). - ML lifecycle: MLflow. - Delivery & serving: co-own and extend the delivery-management service (SDMS), the insight-generation and post-processing services, and ensure they are well-tested and deployable. - Platform & reliability: own the AWS and Prefect delivery platform, manage schema and migrations (PostgreSQL/PostGIS via Alembic), and maintain deterministic, repeata
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Technical stack and responsibilities: - Core language: Python (uv-managed). - Backend services: FastAPI, Uvicorn, SQLAlchemy, Alembic, Pydantic. - Data: PostgreSQL and PostGIS (via GeoAlchemy2). - Cloud: AWS (S3, Lambda, EC2, IAM basics). - Orchestration: Prefect and Ray/Anyscale. - Geospatial: GDAL, Rasterio, GeoPandas, Shapely, STAC (pystac), and COG (rio-cogeo). - ML lifecycle: MLflow. - Delivery & serving: co-own and extend the delivery-management service (SDMS), the insight-generation and post-processing services, and ensure they are well-tested and deployable. - Platform & reliability: own the AWS and Prefect delivery platform, manage schema and migrations (PostgreSQL/PostGIS via Alembic), and maintain deterministic, repeata
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Based on: Data Engineer
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