R&D Data Engineer: Hybrid (Up to 2 Days WFH) – Pipeline & Analytics

avec compétence GmbH; Ecublens; Hybrid; CHF 120,000 - 160,000; Full time

Benefits offered by this job

Up to two days home office

100% workload

3–6 months interim, then permanent

Job summary

Photonics technology is seeking an experienced data infrastructure engineer to turn engineering test data into actionable insights within a deep-tech R&D environment. You will focus on building and maintaining a Python library for data characterization pipelines while ensuring clean abstraction from storage formats and databases.

You will develop scalable, distributed execution solutions, integrate logging and data lineage, and enable robust data export capabilities.

Qualifications

• Master's degree or equivalent practical experience in a relevant field.
• 5+ years of data experience in an R&D, research center, or instrument-heavy environment.
• Strong Python expertise and API/library design experience.
• Proficiency with SQL, Git, and UNIX/bash.
• Experience building ETL/ELT pipelines in production.
• Familiarity with scientific data formats and structured storage.
• Strong written and spoken English skills.

Responsibilities

• Architect a Python library focused on pipeline orchestration for characterization data.
• Ensure abstraction between analysis logic and file formats/storage schemas.
• Develop scalable solutions for local, remote, and distributed execution environments.
• Integrate logging and transformation lineage 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 for end-to-end data traceability.

Skills

Python

Data handling

ETL/ELT

SQL

UNIX/Bash

Git

English

Education

MSc in Computer Science, Engineering, or a scientific discipline

Tools

SQL

Python

Git

UNIX/Bash

ETL/ELT pipelines

Job description

Photonics technology is seeking an experienced data infrastructure engineer to turn engineering test data into actionable insights within a deep-tech R&D environment. You will focus on building and maintaining a Python library for data characterization pipelines while ensuring clean abstraction from storage formats and databases.

You will develop scalable, distributed execution solutions, integrate logging and data lineage, and enable robust data export capabilities.