Forward-Deployed Data Engineer for AI & Genomics

Ellison Institute, LLC; Oxford; Hybride; GBP 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Travel allowance

Bonus

Pension - employer contribution 7.5%

Private medical insurance

Cycle to work scheme

Nursery Salary Sacrifice

Résumé du poste

Ellison Institute of Technology (EIT) seeks a Forward Deployed Engineer to join the Scientific Compute and Data Team in Oxford. You will build scalable data pipelines, work with scientists and engineers on AI, robotics, and biology projects, and help turn raw data into reliable resources.

You’ll own ingestion, storage, and transformation, deploy code in research environments using Docker and Kubernetes, and promote reproducibility and end-to-end ownership across platforms.

Qualifications

• Strong programming experience in Python and data engineering.
• Deep understanding of data storage, sharding, indexing and scalability.
• Experience with cloud compute platforms and Linux environments.
• Experience at scale with distributed data systems.

Responsabilités

• Partner with scientists and engineers to deliver robust, reproducible data pipelines.
• Own ingestion, storage, curation and transformation of diverse biological datasets and formats.
• Package and deploy code in research environments using containers (e.g. Docker).
• Scale processing across distributed cloud warehouses/storage and HPC resources.
• Promote maintainable engineering practices and end-to-end ownership.

Connaissances

Python

Data pipelines

Cloud compute

Linux

Distributed systems

Formation

Science/Engineering background

Outils

Docker

Kubernetes

NextFlow

Description du poste

Ellison Institute of Technology (EIT) seeks a Forward Deployed Engineer to join the Scientific Compute and Data Team in Oxford. You will build scalable data pipelines, work with scientists and engineers on AI, robotics, and biology projects, and help turn raw data into reliable resources.

You’ll own ingestion, storage, and transformation, deploy code in research environments using Docker and Kubernetes, and promote reproducibility and end-to-end ownership across platforms.