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Scientific Software Developer

Telespazio Vega Germany · Darmstadt | Deutschland · Hybrid, Onsite

Gehalt auf Anfrage

Gefunden am 05.06.2026

Match

84%

Fit in Skills, Kultur und Entwicklungspfad.

Beschreibung

Job Zusammenfassung In dieser Rolle entwirfst du Softwarelösungen zur Verarbeitung von Satellitendaten, entwickelst Algorithmen und arbeitest eng mit Experten an der Umsetzung von Earth Observation Missionen und neuen Technologien. Job Zusammenfassung In dieser Rolle entwirfst du Softwarelösungen zur Verarbeitung von Satellitendaten, entwickelst Algorithmen und arbeitest eng mit Experten an der Umsetzung von Earth Observation Missionen und neuen Technologien. Deine Rolle im Team Welcome to Space: We are looking for a Scientific Software Developer with a background in Remote Sensing and Earth Observation or similar fields! Candidates should possess an in-depth understanding of the physics relevant to Earth Observation missions, ideally supported by practical experience. A strong affinity for software development is essential. The successful candidate will work as part of a team of remote sensing specialists to design and implement satellite payload data processing applications for major institutional Earth Observation programs as well as commercial "NewSpace" ventures. Design, develop, and validate satellite payload data processing algorithms and applications. Collaborate with remote sensing experts, scientists and engineers to translate mission requirements into robust software solutions. Contribute to the full processing chain from raw satellite data to higher-level Earth Observation products. Ensure software quality through testing, documentation and version control best practices. Support the integration of applications into operational processing environments. Stay up to date with emerging technologies, programming methods and trends in the space industry. Unsere Erwartungen an dich Ausbildung Master's degree in Physics, Engineering, Computer Science, Remote Sensing, or another relevant discipline. Qualifikationen A PhD in a relevant discipline would be advantageous. Strong background in scientific software development, remote sensing and algorithm design. In-depth understanding of the physics relevant to Earth Observation missions (e.g., radiometry, spectroscopy, radar, atmospheric physics). Proficiency in Python, ideally including Jupyter notebooks, version control (Git) and collaborative workflows. Familiarity with scientific computing libraries and data processing frameworks (e.g., NumPy, xarray, GDAL, rasterio). Ability to work effectively within an interdisciplinary team and communicate complex technical topics clearly. Familiarity with Linux environments and shell scripting. Organised and methodical working style, with strengths in analysis, synthesis, and presentation. Proficiency in English (spoken and written). Familiarity with common data formats (e.g., XML, netCDF, HDF, COG, Zarr). A curious and proactive attitude towards problem solving and exploring new technologies. Erfahrung Practical experience with satellite data exploitation or remote sensing algorithm development. Hands-on experience with containerization technologies (Docker, Kubernetes). Experience with cloud-based computing and parallelization. Previous experience working in the space industry. Unser Angebot This full-time and permanent position with an immediate starting date is based at our headquarters in Darmstadt. Working language is English. Benefits Essen & Trinken ☕️ Kaffee, Tee o. Ä Work-Life-Integration ⏰ Flexible Arbeitszeiten Themen mit denen du dich im Job beschäftigst Cloud Computing AI Metadaten Level: Senior Job Feld: Data, Application Anstellung: Vollzeit Vertragsart: Unbefristetes Dienstverhältnis Arbeitsmodell: Hybrid, Onsite Unternehmenstyp: Etablierte Firma Branche: Internet, IT, Telekom, Luft-, Raumfahrt Ort: Darmstadt | Deutschland

Tech Stack

DockerKubernetesPython

Warum passt du zu dieser Stelle?

Fit technisch: Stark auf Backend und API-Architektur.

Gaps: Fehlende Tool-Erfahrung in 1-2 Schlüsselbereichen.

Success-Wahrscheinlichkeit: Hoch bei schneller Einarbeitung.