Data Engineer (Bioinformatics)

Our Future Health
London
1 month ago
Create job alert

We are hiring 2x Data Engineers (Bioinformatics) to join our Data Engineering Team! As a Data Engineer (Bioinformatics) at Our Future Health, you will have a solid understanding and experience of bioinformatics in particular, tools and methods associated with genomic data. You can design, build and test pipelines using a range of technologies, you can create repeatable and reusable products. You're a strong communicator where you're comfortable working with a multidisciplinary team of Scientists, Software Engineers, Product Managers and other Data Engineers.

What You'll Be Doing:

  • Support the build of data pipelines from data providers to our primary data store and Trusted Research Environment.
  • Produce logic for data transformation steps as code, which meets the requirements for our end users and builds well-curated, accessible and quality-controlled data for analysis.
  • Developing prototypes for pipelines for complex transformations drawing on existing workflows developed in industry and academia.
  • Keep abreast of best practices in data engineering across industry, research and Government and facilitating the adoption of standards.
  • Providing technical input into the upstream parts of the data pipeline, including the specification and transfer of data from data providers.
  • Routine ad-hoc data curation activities requiring hands-on development of bespoke ETL cleaning scripts using languages such as Python.
  • Working with researchers to understand the data requirements and work with them to deliver the data needed for their projects.

Our Future Health will be the UK’s largest ever health research programme, bringing people together to develop new ways to detect, prevent, and treat diseases. We are a charity, supported by the UK Government, in partnership with charities and industry. We work closely with the NHS and with public authorities across all nations and regions of the UK.

Requirements

The successful Data Engineer can listen to the needs of technical and business stakeholders and interpret them and effectively manage stakeholder expectations. To succeed in this role, you will also have some of the following skills:

  • Experience working in an Agile development team
  • Highly proficient in Python
  • Understanding of containerisation using Docker and deployment with Kubernetes
  • Experience with version control (Git/Github)
  • Follow best practices like code review and clean code unit tests
  • Understanding of information governance and data security approaches appropriate for sensitive health data following ISO27001
  • Detailed knowledge and understanding of genomic data
  • Experience using bioinformatics file standards (VCF, BGEN etc) and tools (PLINK, bcftools, QCtools etc)
  • Experience in validating and QCing complex genomic datasets
  • Experience building and maintaining robust, scalable and efficient pipelines capable of processing very large amounts of data from one or multiple systems.
  • You know how to create repeatable and reusable products. 
  • Experience with workflow management tools such as Nextflow, WDL/Cromwell, Airflow, Prefect and Dagster
  • Good understanding of cloud environments (ideally Azure), distributed computing and scaling workflows and pipelines
  • Understanding of common data transformation and storage formats, e.g. Apache Parquet
  • Awareness of data standards such as GA4GH (https://www.ga4gh.org/) and FAIR (https://www.go-fair.org/fair-principles/).
  • Exposure of genotyping and imputation is highly advantageous

Benefits

    • Competitive base salary
    • Generous Pension Scheme – We invest in your future with employer contributions of up to 12%.
    • 30 Days Holiday + Bank Holidays – Enjoy a generous holiday allowance with the flexibility to take bank holidays when it suits you.
    • Enhanced Parental Leave – Supporting you during life’s biggest moments.
    • Career Growth & Development – £500 per year to spend on Learnerbly, our learning platform, plus regular appraisals and development opportunities.
    • Cycle to Work Scheme – Save 25-39% on a new bike and accessories through salary sacrifice.
    • Home & Tech Savings – Get up to 8% off on IKEA and Currys products, spreading the cost over 12 months through salary sacrifice
    • £1,000 Employee Referral Bonus – Know someone amazing? Get rewarded for bringing them on board!
    • Wellbeing Support – Access to Mental Health First Aiders, plus 24/7 online GP services and an Employee Assistance Programme for you and your family.
    • A Great Place to Work – We have a lovely Central London office in Holborn, and offer flexible and remote working arrangements.
  • Join us - let’s prevent disease together.

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.