Clinical Data Engineer

Clinical Data Engineer

Full-Time 36000 - 60000 ÂŁ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and build innovative data engineering and AI solutions for healthcare improvement.
  • Company: Join a leading Health Data Institute committed to transforming patient care.
  • Benefits: Enjoy flexible working, competitive salary, and opportunities for professional growth.
  • Why this job: Make a real difference in healthcare by turning complex data into actionable insights.
  • Qualifications: Proficiency in SQL, Python, and experience in data engineering or analytics required.
  • Other info: Collaborative environment with a focus on diversity and inclusion.

The predicted salary is between 36000 - 60000 ÂŁ per year.

The Clinical Data Engineer will be instrumental in driving the Health Data Institute's mission to leverage data for improved healthcare outcomes. Collaborating with the Principal Data Scientist, Head of Data Science & Advanced Analytics, multidisciplinary teams and Industry Partners, the Clinical Data Engineer will design, build, and operationalise robust data engineering and AI solutions that power advanced analytics and AI initiatives across the Trust and beyond. This position requires strong technical capability in SQL, data pipeline architecture, statistical analysis, machine learning, and predictive analytics, combined with a sound understanding of clinical and operational environments.

The Clinical Data Engineer will be responsible for developing high-quality health datasets, enhancing data infrastructure, and advising internal teams on best practices in data engineering and analytics. As a technical lead and trusted advisor, the Clinical Data Engineer will help curate bespoke datasets for Advanced Analytics, design and develop AI solutions, shape AI policy, support service innovation, and ensure all solutions align with the Trust's Digital Strategy. The ultimate goal is to turn complex data into actionable insights and tools that strengthen patient care, improve operational efficiency, and inform strategic decisions.

Main duties of the job

  • Design, develop, and operationalise data engineering and AI solutions to support research, clinical care, and operational performance across the Trust.
  • Lead the adoption of best practices, develop automated data pipelines, and implement secure, scalable solutions using SQL, Python, R, and cloud technologies.
  • Build predictive and prescriptive models, deploying and monitoring machine learning applications, and applying advanced analytics to improve patient outcomes, service efficiency, and workforce wellbeing.
  • Collaborate with internal teams and external partners, contributing to the Trust's Secure Data Environment and Federated Data Platform, ensuring all work complies with ethical, legal, and governance standards.
  • Manage data research projects, guide stakeholders, and promote adoption of analytics insights to support service transformation.
  • Translate complex technical concepts into actionable recommendations, facilitate workshops and training, and support strategic decision‑making across clinical, operational, and executive teams.

About us

Diversity makes us interesting... Inclusion is what will make us outstanding. Inequality exists and the journey to eliminate it is not easy. Every step we take will be a purposeful step forward to deliver a truly inclusive culture where all our people are enabled to deliver outstanding care, where background is no barrier, and where everyone can be their authentic self and we truly represent our patient community. We are committed to equal opportunities and welcome applications from all sections of the community, regardless of any protected characteristics. Reasonable adjustments will be made for disabled applicants where possible. All applicants who have a disability and meet the minimum criteria for the post can opt for a guaranteed interview.

If you need additional help with your application please get in touch by calling the recruitment team on 0118 322 6997 or 0118 322 5342. Our primary method of communication will be via email. However, if you would prefer to be contacted through a different method, please inform the recruitment team.

Job responsibilities

  • Design, build, and maintain automated, scalable, and secure data pipelines for ingestion, cleaning, transformation, and integration of diverse health datasets.
  • Optimise infrastructure to support analytics, machine learning, and clinical decision support.
  • Implement open‑source, cost‑effective, and cloud‑based solutions where appropriate.
  • Contribute to the Trusts Secure Data Environment and Federated Data Platform for population health and research.
  • Develop and operationalise models to address clinical, operational, and research priorities.
  • Apply modern approaches, including machine learning, NLP, and deep learning, to extract insights.
  • Support deployment into Trust systems, ensuring safe integration with clinical workflows.
  • Monitor models post‑deployment, updating for accuracy, fairness, and compliance.
  • Ensure all work complies with NHS standards for data protection, confidentiality, and security.
  • Promote ethical AI, transparency, and avoidance of algorithmic bias.
  • Work with clinicians, IT, BI, research, and operational colleagues to translate healthcare needs into data solutions.
  • Partner with external organisations including NHS hubs, academic institutions, and industry collaborators.
  • Communicate technical findings to diverse audiences, tailoring language to non‑specialists.
  • Identify and implement opportunities to improve services, patient outcomes, and workforce wellbeing through data.
  • Act as SME for data engineering and AI within the HDI.
  • Mentor analysts, scientists, and placement students in reproducible and code‑based approaches.
  • Plan, manage, and deliver projects from scoping to delivery, applying Agile principles where appropriate.
  • Engage regularly with internal and external stakeholders, including Arcturis, Thames Valley AI Hub, Informatics Research Centre, and University of Reading.
  • Support development and delivery of HDI strategy, aligning with national and regional priorities.

Knowledge, Skills & Experience

  • Degree in Computer Science, Data Science, Statistics, Engineering, or equivalent.
  • Proficiency in Python, SQL, ETL, APIs, and cloud platforms (AWS/Azure/GCP).
  • Knowledge of ML algorithms, operationalisation, and model monitoring.
  • Strong understanding of governance, security, and ethical frameworks in health data.
  • Excellent communication, influencing, and negotiation skills.
  • Experience delivering complex projects and mentoring others.

Desirable

  • Postgraduate qualification (MSc/PhD) in data science, ML, or related subject.
  • Experience with health data standards (HL7, FHIR, SNOMED).
  • Familiarity with NHS datasets and national initiatives.
  • Experience with BI tools such as Power BI, Tableau, or Looker.
  • Research track record with academic or industry partners.

Analytical & Judgement Skills

  • Applies advanced methods to large and complex datasets.
  • Evaluates competing methodologies and balances rigour with operational relevance.
  • Anticipates and mitigates risks such as bias or unintended consequences.
  • Exercises independent judgement in situations of incomplete or conflicting evidence.

Physical, Mental & Emotional Effort

  • Primarily desk‑based role requiring long periods of concentration at a computer.
  • Occasional movement of equipment and travel between sites.
  • Frequent requirement for sustained focus when coding or problem‑solving.
  • Occasional exposure to sensitive or distressing data.
  • Requirement to manage expectations and deliver contentious findings with diplomacy.

Working Conditions

  • Office and hybrid working, with flexibility subject to Trust policy.
  • Use of VDUs for prolonged periods.
  • Occasional regional/national travel to meetings and conferences.
  • Collaborative, multi‑disciplinary working across healthcare, academia, and industry.

Professional Development

  • Active engagement in CPD and knowledge‑sharing.
  • Completion of all mandatory training.
  • Participation in appraisal and development planning.
  • Contribution to training and mentoring of colleagues.

Equality, Diversity & Inclusion

  • Promote fairness, inclusion, and respect in all activities.
  • Ensure solutions are designed and tested for equity and bias reduction.
  • Contribute to a positive and inclusive team culture.

Health & Safety

  • Take responsibility for own health, safety, and wellbeing.
  • Report incidents and hazards promptly.
  • Ensure safe use of equipment and promote a culture of safety across the team.

Other Duties

  • Provide cover during periods of absence or peak demand.
  • Support additional projects and initiatives relevant to the role.
  • Maintain awareness of and compliance with Trust policies.
  • Contribute to continuous service improvement in line with Trust priorities.

Person Specification

  • BSc - Data, Mathematical or Medically related field
  • MSc - Data, Mathematical or Medically related field
  • Project Management Qualification (e.g. PRINCE2)

Experience

  • Minimum 3 years in a Data related field
  • Proficiency in SQL
  • Proficiency in Python (Machine Learning, Deep Learning or LLM Frameworks)
  • Minimum 2 years experience in Data related field
  • Minimum 2 years in a Business or Management Consulting field
  • Experience of Docker, Hadoop, PySpark, Apache or MS Azure
  • Minimum 2 years NHS/Healthcare experience

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.

Clinical Data Engineer employer: Royalberkshire

At the Royal Berkshire Hospital Foundation Trust, we pride ourselves on being an exceptional employer that champions diversity and inclusion while fostering a collaborative work culture. As a Clinical Data Engineer, you will have the opportunity to work at the forefront of healthcare innovation, utilising advanced analytics and AI to enhance patient care and operational efficiency. With a commitment to professional development and a supportive environment, we empower our employees to grow their skills and make a meaningful impact in the community.
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Contact Detail:

Royalberkshire Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Clinical Data Engineer

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.

✨Tip Number 3

Prepare for interviews by practising common questions and scenarios related to data engineering and AI solutions. Be ready to discuss how you've tackled challenges in past projects and how you can contribute to the Trust's mission.

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of our team and contributing to our goals.

We think you need these skills to ace Clinical Data Engineer

SQL
Data Pipeline Architecture
Statistical Analysis
Machine Learning
Predictive Analytics
Python
R
Cloud Technologies
Data Governance
Ethical AI
Communication Skills
Project Management
Stakeholder Engagement
Data Engineering
Advanced Analytics

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Clinical Data Engineer role. Highlight your experience with SQL, data pipelines, and machine learning. We want to see how your skills align with our mission to improve healthcare outcomes!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering in healthcare. Share specific examples of how you've used data to drive insights or improve processes in previous roles.

Showcase Your Technical Skills: Don’t hold back on showcasing your technical skills! Mention your proficiency in Python, R, and any cloud technologies you’ve worked with. We’re looking for someone who can hit the ground running and contribute to our advanced analytics initiatives.

Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and keep track of it. Plus, it shows you’re keen on joining our team at StudySmarter!

How to prepare for a job interview at Royalberkshire

✨Know Your Tech Inside Out

Make sure you brush up on your SQL, Python, and data pipeline architecture skills. Be ready to discuss specific projects where you've used these technologies, as well as any machine learning models you've developed. This will show that you not only understand the theory but can also apply it in real-world scenarios.

✨Understand the Healthcare Context

Familiarise yourself with the clinical and operational environments relevant to the role. Research the Trust's mission and values, and think about how your work as a Clinical Data Engineer can directly impact patient care and operational efficiency. This will help you connect your technical skills to the organisation's goals during the interview.

✨Prepare for Collaboration Questions

Since this role involves working with multidisciplinary teams, be prepared to discuss your experience collaborating with others. Think of examples where you've successfully communicated complex data concepts to non-technical stakeholders or led workshops. Highlighting your ability to engage with diverse audiences will demonstrate your fit for the team.

✨Showcase Your Problem-Solving Skills

Be ready to tackle hypothetical scenarios or case studies during the interview. Practice articulating your thought process when faced with data challenges, such as ensuring compliance with ethical standards or optimising data pipelines. This will showcase your analytical skills and your ability to think critically under pressure.

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