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IRIS – Institut für raumbezogene Infrastruktur und Raumforschung (gGmbH) is seeking a trainee/data engineer to develop Python-based spatial data pipelines and open data workflows. You will work with WFS services, REST APIs, and PostGIS in a collaborative, international setting.
The role emphasizes spatial analysis, Python (GeoPandas, Shapely), and PostGIS, with relocation and housing support offered. A university degree in a relevant field and strong English are required to start.
Organization: IRIS – Institut für raumbezogene Infrastruktur und Raumforschung (gGmbH)
Location: Germany (On-site / Hybrid with Relocation & Housing Support)
Target Program: Opportunity Card (Chancenkarte) / Master Trainees / International Talents
Working Language: English (No initial German language skills required)
The IRIS Institute (gGmbH) is a non-profit, applied research institute dedicated to developing cutting-edge spatial resilience data models and open-data architectures for the energy transition, critical infrastructure, and sustainable regional planning.
We provide comprehensive administrative support for international candidates, including full assistance with the German Opportunity Card (Chancenkarte), degree recognition, and visa procedures. You will receive structured onboarding, local accommodation support, coverage of basic living expenses during training, on-site sponsored German language courses, and access to a modern data engineering tech stack centered on Python, PostGIS, Docker, and GIS platforms.
In this role, you will build and maintain automated Python-based spatial data pipelines connecting to WFS services, REST APIs, and public open-data platforms. You will implement spatial overlay and inference models for energy grid matching and land-use analysis, while validating, structuring, and transforming vector geometries into our central PostgreSQL and PostGIS databases.
We welcome applicants with a completed university degree in Geoinformatics, Computer Science, Data Science, Environmental Engineering, or a related technical discipline. You should bring practical experience or a strong learning interest in Python (GeoPandas, Shapely), SQL databases (PostgreSQL/PostGIS), spatial reference systems, and automated data ingestion workflows. High motivation and fluent English skills are required.