Research Data Engineer

About the role

RelationRx is a TechBio company in London that uses single‑cell multi‑omics, functional assays and machine learning to discover new medicines. As a Research Data Engineer you will design and build the data systems that enable predictive models of cellular behaviour, ensuring that large, multi‑modal datasets are efficiently stored, accessed and processed for analysis and ML training.

Key responsibilities

• Design, build and maintain scalable data pipelines ingesting multi‑modal scientific data.
• Optimise data movement, storage layouts and access patterns for analytical and ML workloads.
• Implement and evolve cloud‑native data lake / lakehouse infrastructure using IaC.
• Provide data versioning, lineage and quality monitoring.
• Collaborate with data scientists, ML scientists and research engineers to define data representations and storage strategies.
• Develop workflow orchestration for production pipelines and large‑scale batch jobs.
• Ensure infrastructure complies with security, audit and governance requirements.
• Champion engineering best practices across the data platform.

Required profile

• Degree in Computer Science, Engineering or a related quantitative discipline.
• Significant industry experience in data engineering, MLOps or data platform roles.
• Proven ability to design data pipelines and storage layouts for large, heterogeneous datasets.
• Experience partnering with scientific or research users and handling experimental data.

Required skills

• Python programming.
• Cloud‑native data infrastructure (AWS S3, GCS) and Infrastructure‑as‑Code (Terraform).
• Data lake / lakehouse technologies and columnar formats (Parquet, Zarr, TileDB, HDF5).
• Distributed processing frameworks (Spark, Polars, Dask, DuckDB).
• Workflow orchestration tools (Airflow, Dagster, Prefect).
• Containerisation and orchestration (Docker, Kubernetes).
• Data versioning, lineage and quality monitoring concepts.