You will build and maintain the analysis library and data infrastructure that turns engineering test data into actionable insights, in a deep-tech R&D environment.

Ihre Aufgaben

Architect a Python library centered on pipeline orchestration for characterization data
Ensure abstraction between analysis logic and underlying file formats or storage schemas
Develop scalable solutions for local, remote, and distributed execution environments
Integrate logging and transformation lineage for dataframes with database export capabilities
Build multi-site infrastructure for test data and metadata storage
Develop ingestion mechanisms for relational database metadata updates
Standardize retrieval and storage conventions to ensure end-to-end data traceability

Was Sie mitbringen

MSc in Computer Science, Engineering, or a scientific discipline, or equivalent practical experience
5+ years of experience working with data in an R&D, research center, or instrument-heavy environment
Strong Python expertise with experience designing libraries and APIs
Proficiency with SQL, Git, and UNIX/bash
Experience building and running ETL/ELT pipelines with modern orchestrators in production
Familiarity with scientific data formats and structured data storage concepts
Strong written and spoken English skills

Rahmenbedingungen

Pensum: 100 %
Arbeitsmodell: Hybrid
Option auf Festanstellung nach dem Einsatz, wenn beide Seiten wollen

Was Sie erwartet

100% workload
Up to two days per week home office
3–6 months interim, then a permanent position

Technologien

Python
SQL
Git
UNIX
bash
Prefect
Airflow
Dagster
HDF5
Zarr
Parquet
Ray

So bewerben Sie sich

Sie bewerben sich mit Ihrem Try&Hire-Profil: Lebenslauf hochladen, Angaben prüfen, Eckdaten und Verfügbarkeit eintragen. Ein kurzes Vorstellungsvideo ist freiwillig, hilft aber. Unser Team meldet sich, wenn Ihr Profil zum Einsatz passt.

Research Data Engineer