National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Engineer

The London Clinic
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Job Description

As the Data Engineer you will work within the Business Intelligence team delivering transformation projects. You will assist in the planning, design, development, testing and implementation of complex healthcare services this will also include reports, visualisations, dashboards, database(s) including healthcare and financial systems source data.

  • Job Type: Full Time, permanent position.
  • Hours: 37.5 hours per week; Mon - Fri within the core hours of 9am - 5.30pm.
  • Location: The London Clinic Head Office – NW1 4LJ (Remote working available).
  • Benefits package: We offer a comprehensive package including a contributory pension scheme (total annual contribution up to 20%), Private Medical Healthcare, 33 days annual leave (inclusive), as well as a wide range of other benefits. We also offer excellent career development opportunities.

Duties & Responsibilities

  • Apply your knowledge of healthcare systems to manage, analyse, and interpret complex data sets, ensuring compliance with healthcare regulations and standards.
  • Utilise advanced SQL coding skills for database management and employ ETL tools to transform and load data efficiently.
  • Implement, manage, and maintain data solutions on Azure and other cloud platforms, ensuring robustness and scalability.
  • Clearly articulate ideas, solutions, and data insights to both technical and non-technical stakeholders. Prepare and present detailed documentation and reports.
  • Conduct in-depth data analysis to inform decision-making. Manage and execute data migration projects with precision and attention to detail.
  • Proactively identify problems and devise effective data-driven solutions. Present and implement these solutions to improve data management and operations.
  • Design and implement automated systems for data processes, enhancing efficiency and accuracy.
  • Apply strong problem-solving skills to tackle complex data challenges, focusing on data cleansing, reconciliation, creating value and optimizing performance.
  • Develop comprehensive documentation for data processes and systems. Prepare reports and presentations for internal use and compliance purposes.
    Be central to the creation and evolution of design, and architecture of new and existing products and product components.
  • Work closely with the relevant teams to identify gaps in the current application landscape and document the existing architecture.
  • Support the Business Intelligence & Engineering Team with Migration Projects and support tasks.
  • Data Modelling of new and existing databases and BI Solutions ensuring best practises are always followed.
  • Be involved in end-to-end development, full lifecycle projects including delivering of reporting solutions.

Skills & Experience

  • Experience of Relational Database implementation, operations and/or solution deployment in Microsoft SQL Server.
  • Proficiency in Azure and other cloud data services.
  • Excellent understanding of SQL Server and the Microsoft development stack, with Cloud Solutions experience using tools such Azure, Data Factory, Fabric.
  • Experience in data architecture as well as working with data warehouses, data modelling techniques, tabular models, security, GDPR and PII data handling principles.
  • Profound knowledge of healthcare data, including privacy and compliance regulations
  • Proven experience in ETL processes, Database Automation Tools, Data Quality and Master Data Management and Power BI Integration and deployment.
    Wherescape Red Experience is an advantage.
  • Proven experience in Power BI Visualisations, Dashboards and Dax.
  • Experience in a data engineering role, preferably within the healthcare sector
  • Excellent communicator, both verbally & written, and self-motivated with the ability to work independently and under pressure with good problem-solving skills.
  • Experience in creating automated data solutions and system designs.
  • Detail-oriented with strong analytical and problem-solving abilities.
  • Ability to work independently and collaboratively in a team environment

The London Clinic has charitable status which is fundamental to our identity and how we operate, enabling our teams to invest in treatments, technology and facilities that benefit our patients, staff and the wider community.

We are committed to safeguarding and protecting all adults at risk, children and young people by implementing robust safer recruitment practices during our selection process. Pre-employment checks are undertaken in accordance with industry standards and regulations, and successful applicants may be required to undertake an Enhanced Disclosure via the Disclosure and Barring Service (DBS). If you would like further information about our safer recruitment policy then please contact a member of our recruitment team.

The London Clinic is proud of its diverse workforce and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. We absolutely welcome applicants from underrepresented groups;

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.