Scientific Data Engineer

Orbis Medicines ApS; København; On-site; DKK 600,000 - 900,000; Full time

Job summary

Orbis Medicines ApS in Copenhagen is seeking a Scientific Data Engineer to build scalable data infrastructure that supports biology, chemistry and data science teams. You will develop systems to capture data accurately, design pipelines, and harmonise data workflows across the organisation.

This role suits someone who loves data and code, with a chemistry or biology background or a software engineering mindset, and who enjoys collaborating with scientists to turn data into reliable,

Qualifications

• Degree in chemistry, biology, bioinformatics or related field.
• 3+ years of industry experience in a scientific environment with hands-on exposure to drug discovery data flow from design through synthesis and testing.
• Proficiency in Python and common data libraries.
• Experience with relational databases and SQL.
• Experience designing data structures for scientific data.
• Strong communication and collaboration with scientists.

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 AIML operations
• Act as the go-to contact for lab scientists using our data products and infrastructure

Skills

Python

SQL

Data structures

Communication

Collaboration

Education

Degree in chemistry/biology/bioinformatics

Tools

Dotmatics

CDD Vault

Revvity Signals

Docker

Git

Job description

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. 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
• 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)