Data Engineer Lab Digitalisation (50–80%)

University of Applied Sciences and Arts Northwestern Switzerland FHNW; Muttenz; Hybrid; CHF 120,000 - 150,000; Full time

Benefits offered by this job

Wide range of university sports

Cultural programme of lectures, events

Mentoring programme for career开发

Job summary

FHNW School of Life Sciences seeks a skilled data engineer to design and implement a scalable data platform for laboratory and research data. You will connect lab instruments and LIMS/ELN systems, and develop automated data pipelines with strong data governance.

You will contribute to applied research projects with industrial partners, collaborating closely with research, lab and IT teams while ensuring data security and compliance.

Qualifications

• Degree (Bachelor/Master) in computer science, data science, bioinformatics or a comparable field.
• Several years of data engineering experience with Python and SQL, workflow tools and containers (Docker).
• Knowledge of relational and NoSQL databases, cloud or on-premise data platforms and API development.
• Experience with laboratory data, instrument integration, LIMS/ELN or regulated (GxP) environments is a plus.
• Good German and good English skills, independent and collaborative work style.

Responsibilities

• Design and build a scalable data platform for laboratory and research data.
• Connect lab instruments and LIMS/ELN via interfaces and standards such as OPC UA.
• Develop and operate automated data pipelines (ETL/ELT) with data quality and metadata management.
• Make data available for analytics, dashboards and machine learning in line with FAIR principles.
• Ensure data security, access control and data integrity; document and train users with IT teams.
• Engage in applied research projects with industrial partners.

Skills

Python

SQL

Workflow tools

Docker

APIs

Relational databases

NoSQL databases

LIMS/ELN

Education

Bachelor/Master in computer science or related

Tools

LIMS/ELN

Job description

Your tasks
We are digitalising our biotech laboratory: lab instruments, databases and analytics are to be brought together on one central data platform. You will play a key role in this.

• Design and build a scalable data platform for laboratory and research data
• Connect lab instruments (e.g. anayltic instruments, spectrometers, bioreactors), existing databases and LIMS/ELN via interfaces and standards such as OPC UA.
• Develop and operate automated data pipelines (ETL/ELT), including data quality, metadata management and versioning
• Make data available for analytics, dashboards and machine learning in line with the FAIR principles
• Ensure data security, access control and data integrity, and document and train users in close collaboration with research, lab and IT teams
• In addition, you will be actively involved in applied research projects with several industrial partners

Your profile

You combine solid software engineering with a passion for the life sciences.

• Degree (Bachelor/Master) in computer science, data science, bioinformatics or a comparable field
• Several years of data engineering experience with Python and SQL, workflow tools and containers (Docker)
• Knowledge of relational and NoSQL databases, cloud or on-premise data platforms and API development
• Experience with laboratory data, instrument integration, LIMS/ELN or regulated (GxP) environments is a plus
• Independent, structured way of working, enjoyment of interdisciplinary collaboration, and good German and good English skills

Your Prospects

The FHNW School of Life Sciences offers state-of-the-art technical, laboratory and office facilities. Contributing to the school’s highly motivating working environment – which is second to none – are its collaboration with a large number of companies and institutions in Switzerland and abroad, a widely varied programme of scientific events, and daily contact with young students in research and teaching. The FHNW is also committed to equal opportunities and the compatibility of private and professional life.

Your Benefits

• Wide range of university sports
• Cultural programme of lectures, concerts, theatre and films
• Established implementation of equal pay
• Targeted promotion of doctoral projects
• Annual working time (42 hours/week) with the option of part-time and teleworking
• Mentoring programme for career development