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# Data Engineer (Forward Deployed)

- **Company:** Ellison Institute, LLC
- **Location:** Oxford, UK
- **Salary:** £77,075.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Software Quality, Computer Programming, Information Engineering, Extract Transform Load (ETL), Data Systems, Shard (Database Architecture), Python (Programming Language), Linux System Administration, Rapid Prototyping Process, Software Deployment, Data Storage Technologies, Apache Spark, Generative AI, Indexer, Core Data, Kubernetes, Data Management, Slurm, Software Version Control, Data Pipelines, Docker
- **Published:** October 4, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5909988957

## About the Role

* You have strong programming experience in Python, and value code quality, reliability, and readability as much as performance.
 * You have a deep understanding of data storage and manipulation: relational systems, sharding and parallelisation, indexing, scalability.
 * You have experience working on cloud compute platforms and varied Linux environments.
 * You have worked at scale, especially on distributed/parallelised data systems.
 * You promote good Data Engineering and Data Management practices as a means of enabling good science - reproducibility, version-control, schema design, lineage, single-source of truth.
 * You think in terms of systems and longevity, not just one-off ETL scripts, and embrace end-to-end ownership from low-level performance to user interfaces.

Our Forward Deployed Engineers will have the opportunity to work on diverse projects, and to expand their skillset, but will add particular value when they can match their data engineering expertise with domain knowledge relevant to a project. We would value:

 * Experience preparing data for ML: pre-training, post-training, and evaluations.
 * Scientific background, with experience or qualifications in genomics, proteomics, or other related fields.
 * Experience in bioinformatics and use of industry-standard tooling such as NextFlow.

## Description

At EIT we are seeking a Forward Deployed Engineer to join our Scientific Compute and Data Team. Forward Deployed Data Engineers are a key interface between our core data systems and the research and engineering projects across EIT. You'll work side-by-side with scientists and engineers in frontier AI and robotics, generative and plant biology, or pathogen surveillance. You will disseminate data engineering best practices into the institutes, ensuring that datasets are accurate, reproducible, versioned-controlled, well-structured, and ready for ML. You will help scientists turn raw information from various sources into high-quality resources, ensuring our technical foundations support the next generation of discovery.

This is a hands-on role for those who thrive on collaborating directly with researchers and engineers, solving problems quickly, and turning complex research requirements into scalable, reliable data pipelines while contributing to the broader EIT platform. We are looking for clear, respectful communicators who are comfortable bringing their own expertise into diverse groups.

Day-to-Day, You Might:

 * Partner with scientists and engineers to deliver robust, reproducible data pipelines that meet research needs across disciplines.
 * Own ingestion, storage, curation, and transformation of diverse biological datasets and formats, such as structured/tabular data, unstructured text, high I/O formats like LMDB/Arrow/HDF5, or domain-specific formats such as fastq/fasta and cif.
 * Package and deploy code in research environments using containers (e.g. Docker).
 * Scale processing across distributed cloud warehouses/storage via container orchestration (e.g. Kubernetes), High-Performance GPU Compute (e.g. Slurm), or distributed compute frameworks (e.g. Spark, Ray).
 * Contribute to an engineering culture that values maintainability, testing, robust system design, and deep collaboration, but allows flexibility for rapid prototyping and responsiveness to changing landscapes.