Genomics Data Operations Engineer

About the role

As a Genomics Data Operations Engineer you will join a small, high‑impact data engineering team that underpins both commercial products and internal scientific research. You will transform large, complex genomic datasets into trusted, analysis‑ready resources that drive drug discovery and predictive healthcare.

Key responsibilities

• Ingest large‑scale genetic and genomic data (GWAS summary statistics, individual‑level genotype and phenotype data) using scripts, automated pipelines and hands‑on processing in a Linux environment.
• Interpret QC metrics, investigate anomalies and apply scientific judgement to resolve data‑quality issues.
• Configure workflow parameters and curate detailed dataset metadata for internal scientists and external customers.
• Collaborate with software engineers in an agile setting to diagnose pipeline issues and continuously improve ingestion and QC processes.
• Contribute to schema design for new data types and help expand the genomic data resource.

Required profile

• Strong background in statistical genetics with hands‑on experience handling GWAS summary statistics or large‑scale genotype/phenotype datasets.
• Ability to apply rigorous scientific judgement to data quality problems.
• Comfort working in a Linux/Unix environment and with automated data pipelines.

Required skills

• Python programming
• Unix/Linux command‑line proficiency
• Shell scripting
• Experience with GWAS summary statistics and genotype/phenotype data processing

What we offer

• Opportunity to work at the intersection of data engineering, genetics and drug discovery.
• Hybrid work model (Oxford or London).
• Collaborative, science‑driven environment.