Scientific Data Engineer (Biotechnology, Copenhagen)

Job summary

This role involves developing scalable data solutions and workflows in the field of preclinical neuroscience, focusing on bioinformatics and in vivo data. The position is crucial for structuring and analyzing diverse preclinical data to support drug discovery efforts for brain diseases.

Qualifications

• Master's or PhD in Bioinformatics, Computer Science, or a related field.
• Proficient in coding with Python and R, with a solid understanding of biological concepts and drug discovery.

Responsibilities

• Build and operate robust data pipelines in the cloud (AWS), utilizing infrastructure as code (AWS CDK).
• Work with complex scientific datasets, including omics and time series data, to create reliable systems and workflows.
• Collaborate with multiple teams to enhance data engineering solutions across in vitro and in vivo domains.

Skills

• Experience with workflow orchestration tools (e.g., Nextflow, Dagster) and containerization (e.g., Docker).
• Familiarity with modern data stack technologies such as Snowflake and dbt.
• Strong collaborative and delivery-focused mindset.

Education

• Advanced degree (Master's or PhD) in a relevant field.

Tools

• AWS, Python, R, Nextflow, Dagster, Docker, Snowflake, dbt.