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Research Data Engineer

Skills

airflowapibashdagstereltetlgitparquetprefectpythonrdbmssqlunixPythonAirflowGitSQL

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.

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

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