Genomics Data Ops Engineer: Build Genomic Pipelines

F-Prime Capital; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

25 days annual leave

Pension scheme

Private health insurance

Enhanced paid family leave

Hybrid working

Cycle-to-Work scheme

Job summary

Genomics is seeking a Data Engineer to join a small, high-impact team in a hybrid role based in London or Oxford. You will transform large genomic datasets into trusted, analysis-ready resources, focusing on data transformation, harmonisation and QC, while applying statistical-genetics judgment.

You will work with Python/Unix environments, contribute to schema design, and collaborate across engineering, data science and product teams to expand the genomic data resource.

Qualifications

• Grounded in human statistical genetics with hands-on experience of GWAS summary statistics and/or large-scale genotype data.
• Proficient in Python and Unix/Linux with experience in data engineering or bioinformatics.
• Strong communication and ability to work across multi-disciplinary teams.

Responsibilities

• Moving data in: ingesting large-scale genetic and genomic datasets through scripting, pipelines and Linux processing.
• Safeguarding quality: interpret QC metrics, investigate anomalies and resolve data-quality issues.
• Getting the detail right: configure workflow parameters and curate dataset metadata for internal scientists and external customers.
• Collaborating: partner with software engineers to diagnose pipelines and improve ingestion/QC processes.
• Growing: contribute to schema design for new data types and expand the genomic data resource.

Skills

Python

Unix/Linux

Statistical genetics

Communication

Data quality analysis

Education

BSc or higher in bioinformatics/computational biology/human genetics

Job description

Genomics is seeking a Data Engineer to join a small, high-impact team in a hybrid role based in London or Oxford. You will transform large genomic datasets into trusted, analysis-ready resources, focusing on data transformation, harmonisation and QC, while applying statistical-genetics judgment.

You will work with Python/Unix environments, contribute to schema design, and collaborate across engineering, data science and product teams to expand the genomic data resource.