Data Engineer

Relation is an end-to-end biotech company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays, and machine learning to drive disease understanding—from cause to cure.

This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting-edge ML capabilities with GSK’s deep expertise in drug discovery, this partnership underscores our commitment to pioneering science and delivering impactful therapies to patients.

We are rapidly scaling our technology and discovery teams, creating a unique opportunity to join one of the most innovative TechBio companies. At the heart of London, our state-of-the-art wet and dry laboratories provide an exceptional environment where interdisciplinary collaboration thrives. Together, we’re pushing the boundaries of drug discovery and transforming groundbreaking science into impactful therapies for patients.

We believe that innovation flourishes through diversity and collaboration. As an equal opportunities’ employer, we are committed to building inclusive teams where everyone can contribute their unique perspectives and thrive. We welcome individuals of all backgrounds, fostering an environment where every team member is empowered to do their best work and reach their highest potential.

By joining Relation, you’ll become part of an exceptionally talented team with extraordinary leverage to advance the future of drug discovery. Your work will help shape our culture, influence our strategic direction, and, most importantly, make a lasting difference in the lives of patients.

Relation is offering an exceptional opportunity in Data Engineering, open to candidates across all experience levels.

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• Build, maintain, and monitor pipelines to transfer lab data into appropriate self-hosted and cloud environments, ensuring clear visibility for stakeholders.
  
• Ingest and integrate bioinformatics and multi-modal data from diverse external sources.
  
• Develop and support reusable ETL workflows to standardise data formats, enrich metadata, and implement versioning and lineage logic.
  
• Enhance FAIR compliance by collaborating with Data Science, Machine Learning, and Wet Lab teams to adopt best practices in data management.
  
• Work with users and stakeholders to integrate data assets into the internal data catalogue and further develop this solution.
  
• Connect lab, external, analytical, and ML data assets into a unified ecosystem.
  
• Automate data quality checks and validation layers during ingestion and transformation to ensure accuracy and reliability.
  
• Enable downstream data exploration tools and visualisation dashboards to promote accessibility and usability for non-technical users.
  
• Support data governance by implementing best practices in access control, data lifecycle management, and compliance (e.g., licensing, privacy).
  
• Develop and refine scalable, fit-for-purpose data models and workflows.
  

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• A Bachelor’s or Master’s degree in engineering, computer science, or a related discipline.
  
• 4–5 years of experience in Data Engineering (DE), Data Science (DS), or similar roles — strong problem-solving skills are valued over job titles.
  
• Proficiency in Python and SQL, with experience using libraries such as Pandas, Polars, Dask, PySpark, and NumPy.
  
• Experience with containerisation (e.g., Docker).
  
• Familiarity with Linux environments.
  
• Knowledge of data modelling, including relational databases, object storage, and non-relational databases.
  
• Understanding of data governance, including access control and licensing.
  
• Experience with data visualisation tools such as Plotly, Seaborn, or D3.js (desirable).
  
• Experience with orchestration frameworks such as Airflow or Prefect.
  
• Exposure to cloud environments — AWS experience is a strong advantage.
  
• Familiarity with distributed computing frameworks such as Spark, Databricks, or Kubernetes (desirable).
  
• Experience working with biological datasets or in biotech/healthcare data environments (bonus).
  
• Familiarity with data cataloguing tools (bonus).
  

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• Curious (e.g., eager to learn about new data types or scientific use cases).
  
• A collaborative team player, able to communicate effectively with stakeholders from diverse backgrounds and technical abilities (Data Science, ML, Governance, Scientists).
  
• Passionate about science and making a meaningful impact for patients.
  
• Self-motivated and driven to succeed.
  
• User-focused: you consider how datasets will be used downstream by both humans and machines.
  
• Comfortable working independently and taking initiative.
  
• Compliance-aware: you understand the importance of secure, traceable, and auditable data workflows.
  

Join us in this exciting role where your contributions will have a direct impact on advancing our understanding of genetics and disease risk, supporting our mission to get transformative medicines to patients. Together, we're not just doing research; we're setting new standards in the field of machine learning and genetics. The patient is waiting!

Relation Therapeutics is a committed equal opportunities employer.

RECRUITMENT AGENCIES: Please note that Relation Therapeutics does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation Therapeutics will not be liable for any fees associated with unsolicited CVs.