At a Glance
- Tasks: Transform and manage large genomic datasets to support drug discovery and healthcare.
- Company: Innovative TechBio company focused on genomics and health data.
- Benefits: Competitive salary, 25 days leave, hybrid work, and continuous learning opportunities.
- Other info: Join a vibrant team culture with flexible working and growth opportunities.
- Why this job: Make a real impact in healthcare by working with cutting-edge genomic data.
- Qualifications: Experience in statistical genetics, Python, and data engineering.
The predicted salary is between 45000 - 55000 £ per year.
Location: Oxford or London (Hybrid)
The Mission: Why We Exist
Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. We are united by a single vision to help people live longer healthier lives, using the power of genomics.
Genomics aims to help people live longer, healthier lives in two ways: super-charging drug discovery and development for novel treatments with our AI-enabled advanced genetic analytics platform, and by helping people understand their personal risk of common chronic diseases through polygenic risk scores - giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time.
Role Purpose
Data is the foundation of everything we do. Our Data Engineering team owns the end-to-end journey of the genomic datasets that power both our commercial products and our internal science – from disease-risk insights that reach real patients, to the discovery of novel therapeutic targets. 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: working within established automated workflows, but bringing the statistical-genetics judgement to know when the numbers don't add up – and the curiosity to find out why. As you grow, you'll take on broader work – helping define schemas for new data types and shaping how we expand our genomic data resource. It's a genuine intersection of data engineering, data modelling and genetics, with real scope to develop across both technical and scientific dimensions.
A Day in the Life
- Moving data in: ingesting large-scale genetic and genomic datasets – GWAS summary statistics, individual-level genotype and phenotype data – through a mix of scripting, automated pipelines and hands-on processing in a Linux environment.
- Safeguarding quality: interpreting QC metrics and diagnostic plots, investigating anomalies, and applying sound scientific judgement to resolve data-quality issues.
- Getting the detail right: configuring workflow parameters and curating dataset metadata so every dataset is correctly represented, fit for scientific use, and clearly described for internal scientists and external customers.
- Collaborating: partnering with software engineers and developers in an agile setting to diagnose pipeline issues, define requirements and continuously improve our ingestion and QC processes.
- Growing: contributing to schema design for new data types and helping expand our genomic data resource alongside science, product and engineering.
Who You Are
- 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, and able to point to real bioinformatics or data-engineering work in a research or commercial setting.
- Confident reading complex data-quality outputs, and able to use scientific judgement to investigate and resolve issues.
- Well organised – happy to plan, prioritise and deliver across competing tasks at pace.
- A strong communicator who works well across multi-disciplinary teams and just as effectively on your own.
- Educated to BSc or higher in a relevant discipline – bioinformatics, computational biology, human genetics or similar – or with equivalent experience.
Your Package
We are committed to providing a transparent, supportive, and rewarding work environment.
Compensation & Growth
- Competitive Salary: Salaries are externally benchmarked annually to ensure top-of-market compensation.
- Clear Career Path: A straightforward, open progression framework means you'll always know the path to promotion and how to achieve your next career goal.
- Continuous Learning: Including external courses and a wide library of L&D materials, because your growth is our success.
Wellbeing & Time Off
- Holiday: 25 days annual leave, plus bank holidays, plus an extra 3-day company-wide shutdown at year-end.
- Financial & Health Security: Robust benefits including a market-leading pension scheme, comprehensive private health insurance for you and your family with NO excess, critical illness, and life assurance.
- Enhanced Leave: Enhanced paid family leave to support all new parents.
Work Environment & Culture
- Flexible Working: Hybrid Working (e.g., From our London, Oxford Office).
- Truly Inclusive Time Off: Our 'Bank Your Bank Holiday' program allows you to exchange public holidays for dates that hold personal or cultural significance to you.
- Vibrant Social Culture: From regular Town Halls and team picnics to organised sports events, our social committee ensures frequent opportunities to connect and celebrate.
- Green Commute: Cycle-to-Work scheme and convenient office locations near major transport hubs.
Ready to Build the Future?
We are dedicated to creating a diverse environment and are proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Genomics Data Operations Engineer employer: F-Prime Capital
At Neo4j, we pride ourselves on being a leading innovator in graph intelligence, offering a dynamic work environment that fosters creativity and collaboration. Our commitment to inclusivity and employee growth ensures that every team member has the opportunity to thrive while contributing to impactful projects that shape the future of data analytics. With a strong focus on relationships and user success, working at our vibrant location means being part of a community that values your contributions and supports your professional journey.
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We think this is how you could land Genomics Data Operations Engineer
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We think you need these skills to ace Genomics Data Operations Engineer
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
