---
title: 'Research Data Engineer at relationrx'
canonical: 'https://feeny.ai/job/research-data-engineer-relationrx-london-snfdqd40d7et'
type: 'job'
last_seen: '2026-09-11'
---

# Research Data Engineer at relationrx

- **Company:** relationrx
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Posted:** 2026-07-16
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/relationrx/346e6cb4-70e3-4f06-93e4-e954143bcebd

## Job description

## About Relation

Relation is a sector defining TechBio 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 from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.

The opportunity Relation is offering an outstanding opportunity for a Research Data Engineer to design and build the data systems that power the next generation of predictive models of cellular behaviour. We generate complex and high-dimensional datasets across modalities at scale. What we can model, and the pace at which we iterate, is determined by the quality of the data layer. This role focuses on making our datasets efficient for analysis and ML model training through deliberate systems design: storage layouts, access patterns, distributed systems to move data from instrument to models, modality-specific format decisions, query and serving layers tuned for GPU-saturated training, and upholding the data contract between the wet lab and ML teams.

Day to day, you will

- Design, build, and maintain scalable data pipelines that ingest multi-modal scientific data.
- Optimise data movement, storage layouts, and access patterns for analytical and ML workloads.
- Stand up and evolve cloud-native data lake / lakehouse infrastructure.
- Implement data versioning, lineage, and quality monitoring.
- Partner with data scientists day-to-day to ensure fast and seamless data workflows.
- Collaborate closely with ML scientists and research engineers to design data representations, storage layouts, and access patterns that enable efficient model training and experimentation.
- Build and operate workflow orchestration for both production pipelines and large-scale batch jobs.
- Ensure infrastructure meets security, audit, and governance requirements.
- Champion engineering best practices across the data platform.
- Contribute to architecture decisions across the broader ML platform, including how compute, data, and training systems integrate.

Professionally, you will have

- A degree in Computer Science, Engineering, or a related quantitative discipline; significant industry experience in data engineering, MLOps, or data platform roles.
- Excellent Python engineering skills.
- Deep experience with cloud-native data infrastructure (AWS S3 / GCS, plus the surrounding ecosystem) and Infrastructure-as-Code (Terraform or equivalent).
- A track record of designing data pipelines and storage layouts for large, heterogeneous datasets.
- Experience building scalable analytical data processing workflows using modern engines and frameworks (e.g. Spark, Polars, Dask, DuckDB, or equivalent), with an understanding of their performance and architectural trade-offs.
- Hands-on experience with workflow orchestration (e.g. Airflow, Dagster, Prefect, or equivalent) and containerised environments (e.g. docker, k8s).
- Working knowledge of modern columnar / scientific data formats (Parquet, Zarr, TileDB, HDF5) and lakehouse technologies.
- Experience partnering closely with scientific or research users and comfortable with the messiness of real-world experimental data.
- Bonus experience: biomedical or genomics data (BAM, FASTQ, AnnData, OME-Zarr); regulated or pharma-partnered environments; data governance, FAIR principles, or research data management; feature store implementations.

Personally, you

- Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
- Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.
- Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.
- Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.
- Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.

Working style & culture at Relation At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting!

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

## About relationrx

## Company Overview
- **One-liner**: Relation Therapeutics is an end-to-end biotech company using single-cell multi-omics and machine learning to discover and develop transformational medicines for devastating diseases.
- **Entity Type**: Private (Seed/venture-backed; total funding $139M)
- **Headquarters**: London, United Kingdom (with offices in Miami Beach, US, and presence in Italy & India)
- **Founded**: 2019
- **Founders**: Charles Roberts, Benjamin Swerner, and Jake Taylor-King

## Core Business
- **Primary industry**: Biotechnology / Drug Discovery & Development
- **Target customers**: B2B – partnerships with large pharma (Novartis, GSK, Deerfield); ultimately patients for its own pipeline
- **Mission**: “Understand human biology in an unprecedented way; discovering therapies that will 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.”

## Products & Services
- **Lab-in-the-Loop Platform**: An integrated technology stack combining single-cell analysis, genomics, and machine learning to identify druggable targets and develop transformational medicines.
- **Pipeline**: Preclinical/early-stage programs in osteoporosis (first indication announced March 2023) and atopic diseases (strategic collaboration with Novartis announced December 2025). Further undisclosed programs advanced via partnerships with GSK and Deerfield Management.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric**: Total funding of $139M (as of 2026); annual revenue estimated at $1.5M (LinkedIn estimate)
- **Notable Investors/Partners**:
  - DCVC, N Ventures (NVIDIA), Magnetic Ventures, Khosla Ventures, Firstminute Capital, Meltwind, Hitachi Ventures, ARK Invest
  - Strategic partners: Novartis (collaboration on atopic diseases), GSK ($15M equity investment and partnership), Deerfield Management (collaboration to form new companies from targets)
  - Grant from Bill & Melinda Gates Foundation (2020)
- **Growth Signals**:
  - Headcount grew 51.8% YoY to ~97 employees (LinkedIn)
  - Opened new labs in London (opened Feb 2023 by Nobel laureate Sir Paul Nurse)
  - Access to NVIDIA’s CAMBRIDGE-1 supercomputer
  - Multiple new funding rounds: $25M seed (June 2022), $35M seed-2 (March 2024), $15M from Novartis (Dec 2024), $26M further investment (2026)
  - Active job postings: 17 positions (as of mid-2026), with monthly postings up 54.5%

## Competitive Advantages
- **Differentiated platform**: Proprietary “Lab-in-the-Loop” approach that integrates wet-lab single-cell assays with machine learning, enabling high-resolution target discovery directly from patient tissue.
- **Top-tier compute**: Exclusive access to NVIDIA’s most powerful UK supercomputer and deep partnerships with NVIDIA, Mila, and academic leaders.
- **World-class talent**: Scientific advisory board includes Nobel laureate-level researchers and professors from MIT, Stanford, ETH Zurich, and Oxford; team drawn from GSK, BenevolentAI, Wellcome Sanger, and top universities.
- **Pharma validation**: Strong collaboration and equity investments from Novartis, GSK, and Deerfield signal confidence in the platform and pipeline.

## Strategic Focus
- **Priority areas**: Advancing internal pipeline in osteoporosis and atopic diseases; expanding collaborations with pharma to co-develop novel therapeutics; continuing to invest in AI/ML capabilities and single-cell technology.
- **Growth direction**: Scaling the team (especially in machine learning, data science, and biology), forming new spin-out companies with Deerfield, and deepening the use of generative AI for drug design.

## Why Work Here
- **Culture**: Emphasizes collaboration, empowerment, compassionate candor, and a winning attitude. “We set ambitious goals pushing boundaries with a high-performing mindset.”
- **Team**: Highly interdisciplinary – biologists, ML engineers, data scientists, computational chemists, and drug developers working together under one roof.
- **Location**: London HQ with hybrid possibility for some roles; research roles require on-site lab work (lab in King’s Cross area).
- **Perks**: Not publicly detailed, but the company offers the chance to work on cutting-edge AI + biology problems, access to NVIDIA supercomputing, and the impact of bringing new medicines to patients.
- **Engineering/Research Culture**: Strong focus on open collaboration with academia (e.g., Mila, Scripps, Gates Foundation); active hiring for senior ML scientists, computational biologists, and data engineers.

## Sources
1. [relationrx.com](https://www.relationrx.com/)
2. [relationrx.com/careers](https://www.relationrx.com/careers)
3. [relationrx.com/about](https://www.relationrx.com/about)
4. [LinkedIn – Relation Therapeutics](https://uk.linkedin.com/company/relation-therapeutics)
5. [jobs.ashbyhq.com/relationrx](https://jobs.ashbyhq.com/relationrx)

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