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.

Your tasks

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

What you bring

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

Conditions

Workload: 100 %
Work model: Hybrid
Option of a permanent position after the assignment if both sides want it

What to expect

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

Technologies

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

How to apply

You apply with your Try&Hire profile: upload your CV, check the details, enter key facts and availability. A short introduction video is optional but helps. Our team will get in touch if your profile fits the assignment.

Research Data Engineer