Data Engineer

02nd October, 2026

Principal Scientist – Multi-Omics Data Engineering
Location: South Germany | Hybrid, 2–3 days onsite per week
Contract: Permanent

Kemio is supporting a pharmaceutical organisation seeking an experienced data engineer to help turn complex biological data into reliable resources for drug discovery.

Working closely with computational biologists and AI/ML specialists, you’ll build scalable pipelines that process and integrate multi-omics data, supporting target identification and the development of new therapies.

This is an opportunity to combine hands-on engineering with scientific impact, at Principal Scientist level.

The role

• Design, build and maintain scalable pipelines across proteomics, single-cell RNA sequencing, spatial omics and metabolomics.
• Deliver consistent, high-quality datasets for computational biology and AI/ML research.
• Establish standards for data processing, quality, integration and delivery, working with internal teams and external partners.
• Apply agentic AI to improve data ingestion, engineering and workflow automation.
• Develop and improve research databases, computational pipelines and reusable data assets.

At Principal Scientist level, you’ll also shape the organisation’s approach to omics data engineering, lead cross-functional initiatives, establish partnerships to bring high-quality human datasets into the organisation, and mentor scientists and engineers.

What we’re looking for

• A PhD in Bioinformatics, Computational Biology, Computer Science or a related discipline, AND several years of relevant industry experience (5 plus years for principal)
• A strong track record of building scalable pipelines for omics data processing.
• Strong experience with one or more of the following data types: single cell, spatial, bulk, proteomics, metabolomics, or genomics.
• Excellent programming skills in Python or R.
• Experience with workflow tools such as Nextflow or Snakemake and cloud platforms such as AWS or Azure.
• Familiarity with container technologies such as Docker or Kubernetes.
• Experience using agentic AI to automate data workflows would be an advantage.

For the Principal Scientist appointment, you’ll bring extensive pharmaceutical or biotech experience, evidence of leading complex projects and influencing technical strategy, and expertise in integrating multiple omics modalities and applying advanced AI/ML approaches to data analysis.

Your work will directly support scientists using complex biological data to discover new medicines. You’ll combine practical engineering ownership with opportunities to improve how multidisciplinary research teams access, process and use data.