Geospatial Data Engineer & Spatial Pipelines (m/f/d)

Arbeitsagentur; Bad Grönenbach; Hybrid; EUR 70.000 - 100.000; Vollzeit

Benefits dieser Stelle

Master/Trainee Track

Accommodation & Onboarding

Visa & Residency Support

Modern Tech Stack

Zusammenfassung

Project IRIS in Germany seeks a Geospatial Data Engineer to build automated pipelines connecting to WFS services and REST APIs, deploying robust spatial analyses in a production setting.

You will refine data models, ensure EPSG:25832 harmonization, containerize services with Docker, and operate within a PostGIS-based secure server environment.

Qualifikationen

• Degree in Geoinformatics, Computer Science, Data Science or equivalent practical experience.
• Strong Python skills with GeoPandas and Shapely.
• Experience with PostgreSQL/PostGIS and spatial data modeling.

Aufgaben

• Develop automated pipelines connecting to WFS services, REST APIs, and public open-data platforms.
• Implement spatial overlay models and energy grid matching within PostGIS.
• Harmonize complex vector geometries to EPSG:25832 before database insertion.
• Containerize services with Docker and deploy to secure server infrastructure.

Kenntnisse

Geospatial data modeling

Python programming

GeoPandas / Shapely

Docker deployment

Ausbildung

Geoinformatics / Computer Science / Data Science degree

Tools

PostgreSQL

PostGIS

WFS & REST APIs

Jobbeschreibung

Geospatial Data Engineer & Spatial Pipelines (m/f/d)

Location: Germany (Hybrid / Remote options available)

Contract Type: Full-Time Employment (Permanent)

Target Group: Software Engineers, Data Engineers, Opportunity Card (Chancenkarte) Holders, and Master's Graduates

About Project IRIS

Project IRIS is an applied research and technology initiative dedicated to automated spatial data analysis, cadastre intelligence, infrastructure mapping, and open-source data modeling. Together with our commercial transfer network, we bridge the gap between academic data science, resilience research, and practical real-world application. Complex geospatial and resilience data models are deployed into active enterprise environments and infrastructure tools. In this role, you turn algorithmic frameworks and spatial datasets into robust, production-ready digital architectures.

Your Focus & Responsibilities

• Geospatial Data Modeling: Develop and refine automated pipelines connecting to WFS services, REST APIs, and public open-data platforms.
• Spatial Inference: Implement spatial overlay models for energy grid matching and land analysis directly within our PostGIS cluster.
• Data Harmonization: Validate, clean, and transform complex vector geometries into a single coordinate reference system (EPSG:25832) before database insertion.
• Cloud Deployment: Package services into robust Docker environments and deploy them on secure server infrastructure.

What We Are Looking For

• Technical Background: Degree in Geoinformatics, Computer Science, Data Science, or equivalent practical industry experience.
• Core Technical Skills: Solid programming foundation in Python (GeoPandas, Shapely) and relational databases (PostgreSQL/PostGIS).
• Mindset: Strong analytical curiosity, proactive problem-solving attitude, and a clean-code engineering approach.
• Eligibility: Open to local applicants and international candidates currently in or moving to Germany (e.g., Chancenkarte / Opportunity Card).
• Languages: Professional working proficiency in English (required); German language skills are a plus.

What We Offer

• Full-Time Permanent Employment: Long-term career stability with clear growth trajectories.
• Dual Master / Trainee Track Available: Tailored tracks including academic coordination and complete tuition support for candidates combining practice with academics.
• Accommodation & Onboarding Package: Structured assistance with local accommodation, official registration, and comprehensive onboarding.
• Visa & Administrative Backing: Dedicated employer support for Opportunity Card conversions and German residence/work permit applications.
• Modern Work Environment: Work in a high-efficiency tech stack focused on high-value architecture rather than boilerplate tasks.