Earth Observation (EO) & Remote Sensing Engineer (m/f/d)

Arbeitsagentur; Bad Grönenbach; Hybrid; EUR 65.000 - 90.000; Vollzeit

Benefits dieser Stelle

Accommodation & onboarding package

Visa & administrative backing

Zusammenfassung

Arbeitsagentur in Germany is seeking an Earth Observation and Remote Sensing Engineer (m/f/d) to join the Project IRIS initiative. You will build pipelines to fetch Sentinel-1/2 data and develop algorithms to detect surface changes and thermal anomalies, integrating results into a PostGIS database.

The role requires a degree in Remote Sensing or related fields and strong Python tooling experience (Rasterio/xarray/GDAL).

Qualifikationen

• Degree in Remote Sensing, Geoinformatics, Data Science, Physics, or equivalent practical industry experience.
• Deep practical experience in processing satellite data (Landsat, Sentinel) using Python libraries such as Rasterio, xarray, or GDAL.
• Analytical mindset to derive ecological, thermal, and structural factors from raw pixel values.

Aufgaben

• Build automated pipelines to fetch and process Sentinel-1 (Radar/InSAR) and Sentinel-2 (Multispectral) data via Copernicus Data Space Ecosystem.
• Develop algorithms to automatically detect surface changes, vegetation decline, moisture indices (NDVI/NDWI), and thermal anomalies.
• Integrate derived raster metadata and Cloud-Optimized GeoTIFFs (COG) into the central PostGIS vector database.

Kenntnisse

Sentinel-1 & InSAR processing

Sentinel-2 processing

Python (Rasterio, xarray, GDAL)

PostGIS / spatial DB

Ausbildung

Degree in Remote Sensing / Geoinformatics

Tools

Rasterio

xarray

GDAL

Jobbeschreibung

Earth Observation (EO) & Remote Sensing Engineer (m/f/d)

Location: Germany (Hybrid / Remote options available)

Contract Type: Full-Time Employment (Permanent)

Target Group: Remote Sensing Specialists, Data Scientists, Physicists, Opportunity Card Holders, and Master's Graduates

About Project IRIS

Project IRIS develops AI-supported spatial resilience and geospatial data models for the energy transition. To breathe dynamic life into our static infrastructure data, we integrate global earth observation data into our central inference engine. In this role, you will add the dimension of real-time surface activity and physical states to our spatial intelligence models.

Your Focus & Responsibilities

• Satellite Pipelines: Build automated pipelines to fetch and process Sentinel-1 (Radar/InSAR) and Sentinel-2 (Multispectral) data via the Copernicus Data Space Ecosystem.
• Algorithm Development: Develop algorithms to automatically detect surface changes, vegetation decline, moisture indices (NDVI/NDWI), and thermal anomalies.
• Data Integration: Seamlessly integrate derived raster metadata and Cloud-Optimized GeoTIFFs (COG) into our central PostGIS vector database.

What We Are Looking For

• Technical Background: Degree in Remote Sensing, Geoinformatics, Data Science, Physics, or equivalent practical industry experience.
• Core Technical Skills: Deep practical experience in processing satellite data (Landsat, Sentinel) using Python libraries such as Rasterio, xarray, or GDAL.
• Mindset: An analytical mindset capable of deriving tangible ecological, thermal, and structural factors from raw pixel values.
• Eligibility: Open to local applicants and international candidates (Chancenkarte / Opportunity Card supported).
• 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.
• Accommodation & Onboarding Package: Structured assistance with local accommodation, official registration, and comprehensive onboarding.
• Visa & Administrative Backing: Dedicated employer support for Opportunity Card conversions and visa applications.
• Modern Tech Environment: Work in a high-efficiency environment focused on cutting-edge geospatial intelligence.