Data Engineer (AI Enablement)
Job summary
Do you want to build the infrastructure that brings advanced analytics and AI from theory into reality? University College London Hospitals is looking for a Data Engineer (AI Enablement) to join the SAFEHR team.We are solving hard problems: building the secure, modern data infrastructure that lets advanced research and machine learning move from theory into reality. You will design data pipelines, evolve our data warehouse and metadata capabilities, prototype machine-learning workflows on real clinical data, and support data quality across the Trust. Our stack includes R, Python, and SQL; with an ongoing move to a modern data platform. We develop our work as open source wherever feasible.You'll work alongside clinicians, researchers, and engineers on projects that directly improve patient care. Day to day, that means hands-on data engineering: building and improving pipelines, coordinating metadata systems, mentoring junior staff, and working with clinical experts and researchers. This role would also be well suited to a research software engineer with an interest in data engineering.The position is classified at Grade 7, offering a competitive salary (£58,133 - £65,261). If you want real-world data engineering challenges, serious technical development, and a direct line from your work to patient outcomes, we'd like to hear from you.
Main duties of the job
Data Pipelines
You will design, build, and maintain data pipelines that give clinicians, researchers, and operational teams reliable, timely access to UCLH's clinical data.
Data Warehousing and Transformation
You will develop and improve UCLH's data warehouse environments. Being involved in the transition from using an R-based data pipeline to Spark jobs running on a data platform. You will model and transform data from our Epic electronic health record system, coordinating closely with stakeholders to maintain robust metadata. Where existing systems carry technical debt, you will be expected to show initiative in proposing and delivering re-engineering work.
Data Quality and Documentation
You will specify and build reports that measure data quality. You will also develop documentation that enables the scalable, correct use of clinical datasets by reporting teams, clinical users, and research projects.
Collaboration and Open Source
You will work within a multidisciplinary team spanning engineers, clinicians, and data scientists, and collaborate with partners including UCL's Advanced Research Computing Centre and UCLH's Information Services teams. We develop our software as open source where feasible, and you will be expected to contribute to that culture through code reviews, automated testing, and clear, shareable code.
About us
University College London Hospitals NHS Foundation Trust (UCLH) is one of the most complex NHS trusts in the UK, serving a large and diverse population. We provide academically led acute and specialist services, to people from the local area, from throughout the United Kingdom and overseas. Our vision is to deliver top-quality patient care, excellent education, and world-class research.
We provide first-class acute and specialist services across eight sites:
University College Hospital (incorporating the Elizabeth Garrett Anderson Wing)
National Hospital for Neurology and Neurosurgery
Royal National ENT and Eastman Dental Hospitals
University College Hospital Grafton Way Building
Royal London Hospital for Integrated Medicine
University College Hospital Macmillan Cancer Centre
The Hospital for Tropical Diseases
University College Hospital at Westmoreland Street
We are dedicated to the diagnosis and treatment of many complex illnesses. UCLH specialises in women's health and the treatment of cancer, infection, neurological, gastrointestinal and oral disease. It has world class support services including critical care, imaging, nuclear medicine and pathology.
Job description
Job responsibilities
For the full Person Specification and more information regarding the main responsibilities of this role, please refer to the attached Job Description.
Please note, due to anticipated high volumes of applications, this vacancy may close earlier than the listed closing date. You are advised not to delay submitting your completed application
Come and be a part of the best NHS trust in England to work for, according to our staff*
* UCLH top trust to work at in England - In the most recent NHS staff survey UCLH had the highest percentage of staff who said they would recommend us as a place to work, out of all general acute or acute/community NHS trusts in England for the third year in a row.
UCLH recognises the benefits of flexible working for staff To find out more, visit: Flexible working.
To discover more about what makes UCLH a great place to work, visit: Why Choose UCLH?
Person Specification
Knowledge and Qualifications
- Educated to Masters degree level or equivalent professional experience
- Understanding of data retrieval, processing and information analysis within health care
Experience
- Significant experience in a data or information role
- Experience of working with relational databases and SQL
- Well versed in Git and modern data-engineering development standards, including code reviews, automated testing and data validation.
- Proven track record deploying and monitoring machine learning solutions on clinical datasets (e.g., risk stratification, patient flow, phenotyping), including validation, drift monitoring, and adherence to clinical safety and data governance standards.
- Experience of using R or Python
- Experience with modern data engineering tools and frameworks (e.g. dbt, snowflake, spark, etc.)
- Experience in an NHS informatics role or other healthcare information environment
Skills and Abilities
- In depth specialist knowledge of information analysis and the use of information acquired through degree or equivalent experience
- Ability to interrogate databases and solve complex problems
- Proven ability to acquire knowledge and skills of new technologies
- Intermediate use of R or Python
- Ability to independently interpret the requirements of information users and present detailed, complex reports that can be understood by a wide audience.
- Understanding of data quality issues and how these relate to the organisation as a whole
- Strong software engineering fundamentals (design patterns, SOLID principles) or data modelling (data modelling patterns, dimensional modelling, data warehousing)
- Ability to collaborate with others, working closely with engineering teams
Communication
- Ability to communicate effectively with staff at all levels
- Excellent Oral and Written Communication Skills
- Ability to train other staff in the use of technologies
- Ability to communicate on issues which can be complex and multi-stranded.
- Effective leadership of staff
Planning and Organisation Skills
- Ability to plan, prioritise and meet deadlines
- Ability to take responsibility for own workload
Disclosure and Barring Service Check
This post is subject to the Rehabilitation of Offenders Act (Exceptions Order) 1975 and as such it will be necessary for a submission for Disclosure to be made to the Disclosure and Barring Service (formerly known as CRB) to check for any previous criminal convictions.
Certificate of Sponsorship
Applications from job seekers who require current Skilled worker sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas and Immigration website.
From 6 April 2017, skilled worker applicants, applying for entry clearance into the UK, have had to present a criminal record certificate from each country they have resided continuously or cumulatively for 12 months or more in the past 10 years. Adult dependants (over 18 years old) are also subject to this requirement. Guidance can be found here Criminal records checks for overseas applicants.
Employer details
Employer name
University College London Hospitals NHS Foundation Trust
Address
University College London Hospital
250 Euston Road
London
NW1 2PG
Employer's website
https://www.uclh.nhs.uk