Research Data Engineer

Try&Hire; Ecublens; Hybrid; CHF 90,000 - 120,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Try&Hire is seeking a senior data engineer to build and maintain the analysis library and data infrastructure that turns test data into actionable insights in a deep-tech R&D environment.

You will architect a Python library for pipeline orchestration, ensure abstraction from file formats, and enable scalable local, remote, and distributed execution. This role emphasizes data traceability and production-grade ETL.

Qualifications

• MSc or equivalent in a relevant field
• 5+ years of data experience in an R&D environment
• Strong Python and API/library design experience
• Proficient SQL, Git, and UNIX/bash

Responsibilities

• 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

Skills

Python programming

English communication

Data analysis and modeling

Education

MSc in Computer Science, Engineering, or a scientific discipline

5+ years data in R&D environment

Tools

SQL

Git

UNIX/bash

Prefect

Airflow

Dagster

HDF5

Zarr

Parquet

Ray

Job 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