Genomics Data Operations Engineer
GenomicsGenomic Medicine company
Oxford, United KingdomMid
F-Prime Capital
Foresight Partners
Infinity Investment Partners
MassMutual
ARCH Venture Partners
Foresite Capital
Data & AI
About the role
TL;DR
Transform large genomic datasets into analysis-ready resources with a focus on quality and scientific accuracy.
- •As a Data Engineer in this small, high-impact team, you'll turn large, complex and scientifically consequential datasets into trusted, analysis-ready resources.
- •Your focus will be data transformation, harmonisation and quality control.
- •Key Responsibilities Ingesting large-scale genetic and genomic datasets through automated pipelines in a Linux environment.
- •Interpreting QC metrics, investigating anomalies, and resolving data-quality issues using scientific judgement.
- •Configuring workflow parameters and curating dataset metadata.
- •Partnering with software engineers to diagnose pipeline issues and define requirements.
- •Contributing to schema design for new data types.
- •Requirements Grounded in human statistical genetics, with hands-on experience of GWAS summary statistics and/or large-scale individual-level genotype and phenotype data.
- •Proficient in Python and Unix/Linux.
- •Confident reading complex data-quality outputs and using scientific judgement to resolve issues.
- •Well organised and able to plan, prioritise and deliver across competing tasks at pace.
- •Strong communicator who works well across multi-disciplinary teams.
- •Educated to BSc or higher in a relevant discipline or with equivalent experience.
Required skills
PythonBashLinuxGitSQL
Nice-to-have skills
DockerKubernetesAWSGoogle CloudAzure
Domain expertise
biotechhealthcare
Benefits & perks
Competitive Salary, Clear Career Path, Continuous Learning, 25 days annual leave, 3-day company-wide shutdown at year-end, Private health insurance, Critical illness cover, Life assurance, Enhanced paid family leave, Hybrid Working, Bank Your Bank Holiday program, Cycle-to-Work scheme
Tech stack
PythonBashLinuxGitDockerKubernetesAWSGoogle CloudAzureSQL