Description
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.
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
Profile
- 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
Offer
- 100% workload
- Up to two days per week home office
- 3–6 months interim, then a permanent position
Company
Photonics technology