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Data Engineer

Pubblicato il 10-10-2026 - MetaSensing in Milano

Job purpose:
to build the data infrastructure supporting our AI/ML pipeline for Synthetic Aperture Radar (SAR) object detection. Working closely with our AI/ML Engineer, you will manage the ingestion, processing, and organization of massive airborne, spaceborne, and simulated radar datasets.
Company description:
MetaSensingis an innovative Italian remote sensing company founded in 2008 with the aim of commercializing the new compact, high resolution radar mapping technology.
In just a few years,MetaSensinghasacquirednumeroussuccessful airborne radar campaigns completed at the Ka, Ku, X, C, S, L and P frequency bands, and developed drone and space-based radar systems for different applications.
TodayMetaSensingis one of the unique companies in the world which offer cost effective airborne and space-based radar sensors and services both for commercial and security applications.
Combination of innovative technology and advanced processing techniques has madeMetaSensingafast growing, global company with projects in Europe,South EastAsia, Middle East, North and South America.
Job Duties:




- Build automated data pipelines to ingest, parse, and process high-volume SAR datasets from satellite and airborne platforms
- Partner with the AI/ML Engineer to transform raw radar imagery into clean, model-ready formats for deep learning training and validation
- Manage spatial databases and large-scale storage systems for efficient data querying and retrieval
- Integrate simulated SAR data workflows into the core training data pipeline
- Optimize data flow and storage architectures to eliminate training bottlenecks

Required skills and qualifications:
- Strong proficiency in Python and SQL, with a solid grasp of spatial data structures and raster/vector data handling
- Experience with cloud storage, containerization, and data pipeline orchestration tools
- Experience working with large image datasets, including preparation and quality control
- 2+ years of hands-on data engineering e

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