Scientific Data Engineer - to build… at Orbis Medicines · Frederiks…

Scientific Data Engineer - to build systems and structures

Location: Frederiksberg

Orbis is growing fast. As our biology and chemistry teams grow, we need our data infrastructure to scale as well. We are looking for a Scientific Data Engineer to build systems and structures that capture data accurately and smoothly so that the science team can focus on the science.

About the role

You’ll work closely with biology, chemistry, design and data science teams to understand how they work and what they need from their data, identify areas for improvement and then build solutions using both commercial and custom tools.

This is a chance to join a growing biotech company at a crucial moment as we invest in our lab and data infrastructure, helping build a cutting-edge data platform, designing workflows and building pipelines. This role would suit someone who loves data and code. Someone with a chemistry or biology background with a computational focus, or a software engineer with experience working in a scientific environment.

You will be working onsite in Copenhagen.

Responsibilities

• Develop and manage the Orbis data platform, spanning commercial software and custom solutions, including implementing new systems and migrating existing data
• Work with chemistry, biology and data science teams to gather requirements, prototype solutions, and harmonise data operations across the organisation
• Write and maintain ETL data pipelines to streamline data ingestion and organisation
• Safeguard data integrity and quality in line with FAIR principles
• Collaborate with software engineers and data scientists to enable AI&ML operations
• Act as the go-to contact for lab scientists using our data products and infrastructure
  
  

Qualifications & experience

• A degree in chemistry, biology, bioinformatics or a related field
• A strong passion for data in drug discovery
• 3+ years of industry experience in a scientific environment, with hands-on exposure to drug discovery data and how it flows from design through synthesis and testing
• Good working knowledge of Python and common data libraries
• Experience with relational databases and SQL
• Experience designing data structures for scientific data
• Strong communication skills and a track record of working collaboratively with scientists
  
  

Nice to have

• Experience with cloud infrastructure (AWS or GCP)
• Software engineering practices such as Git, CI/CD, Docker and code testing
• Experience with ELN or LIMS systems (e.g. Dotmatics, CDD Vault, Revvity Signals)

Application

Please contact Talent Acquisition Partner Mia Danielsen (part of

DEDENROTH) if you have any questions about the role or the process.

Phone: +45 26178142

Email: mia.danielsen@orbismedicines.com

More about Orbis Medicines

The Orbis’ nGen platform designs macrocycles with oral bioavailability by combining AI technologies with automated synthesis and high-throughput screening of real compounds.

Orbis Medicines has been awarded a 2025 Endpoints 11 title as one of biopharma's most exciting start-ups. This marks the first time a Nordic biotech has received this honor – highlighting the disruptive potential of Orbis Medicines. With a recent EUR 90 million Series A funding round, led by top-tier investors such as NEA, Eli Lilly, Cormorant, the Export and Investment Fund of Denmark and founding investors Novo Holdings and Forbion, Orbis Medicines are well-positioned for significant growth and long-term success. The confidence of these investors validates the potential to bring groundbreaking therapies to the market.

Orbis Medicines has an established R&D site in Copenhagen that includes a state-of-the-art laboratory and a team of +40 experienced professionals and scientists. We offer the excitement of a start-up, opportunities for professional growth, and the opportunity to be at the forefront of biotech innovation. Your ideas and contributions will shape the future of medicine. Please visit the website for more details www.orbismedicines.com.