Sr Data Engineering Professional, Omics Data

As a Sr Data Engineering Professional, you will design and operate data pipelines and Omics data products that enable researchers to extract insights from complex biological data. You will bridge engineering and biology, partnering with scientists to support target and biomarker discovery. You’ll contribute to scalable data platforms and ensure quality, governance, and reproducibility. This role offers impact across research, product areas, and platform architecture in a collaborative, international setting.

• learning and development opportunities
• inclusive recruitment process
• equal opportunities for all applicants
• global company culture and collaboration

• Engineer analysis-ready biological data solutions for computational biologists, geneticists, data scientists, and AI/ML engineers
• Build and operationalise Omics data products and analytical workflows across transcriptomics, single-cell omics, CRISPR/functional genomics, proteomics and multi-omics datasets
• Build and maintain Statistical Genetics pipelines (GWAS ingestion/harmonisation, annotation, fine-mapping, colocations, Mendelian randomisation, gene prioritisation workflows)
• Ensure data quality, reproducibility, traceability and governance through automated validation, monitoring, lineage, testing, and release management
• Contribute to future-state data platform architecture and engineering best practices within the team
• Develop as a recognised expert for your product area and foster cross-functional partnerships to enable scalable data ecosystems for scientific innovation

• Significant hands-on experience in data engineering or bioinformatics engineering
• Proven track record building/operating production data pipelines for Omics/Genetics datasets
• Cloud computing proficiency and programming/workflow tools (Python, R, Bash, SQL, Nextflow, Airflow, Databricks)
• Expertise in ETL, data pipelines, metadata harmonisation, data lifecycle management, data product release processes, and operational support
• Experience operationalising analytical workflows (differential expression, gene set/pathway enrichment, single-cell analysis, GWAS harmonisation, fine-mapping, colocalisation)
• Hands-on data modelling, metadata design, lineage, quality controls and efficient biological database design
• Excellent stakeholder management and ability to explain complex topics to technical and scientific audiences
• Comfort working in evolving processes with distributed ownership, collaboration, pragmatism and strong problem-solving skills

• Stakeholder management
• Clear communication
• Collaboration
• Python
• R
• Bash