At a Glance
- Tasks: Lead the design and operation of a cloud-based data platform for analytics and AI.
- Company: Join a forward-thinking organisation committed to population health and outcomes.
- Benefits: Enjoy NHS pension, flexible working, training opportunities, and a collaborative environment.
- Other info: Diverse and inclusive workplace with strong commitment to professional growth.
- Why this job: Make a real impact on health outcomes while advancing your career in data engineering.
- Qualifications: Master's in Computer Science or equivalent experience in data engineering and cloud platforms.
The predicted salary is between 63000 - 77000 £ per year.
As Senior Data Engineer - Connected Care, you will lead the design, build and operation of a cloud-based data platform to enable analytics, population health intelligence and AI-enabled use cases. You will provide technical leadership and hands-on delivery for scalable data pipelines and integration services, primarily on Azure, while mentoring others. The role supports senior stakeholders and requires shaping secure, reliable data assets to support the organisation’s population health and outcomes-focused mission. You will work closely with the Head of Data Engineering to drive standards and continuous improvement, delivering tangible impact across the enterprise data platform.
Pay / Benefits
- NHS Pension Scheme
- Agile and flexible working
- Access to training and career progression
- Collaborative multidisciplinary environment
- Diversity and inclusion commitment
Responsibilities
- Design, build and maintain scalable, secure data pipelines to support analytics, reporting, population health and AI use cases
- Lead technical delivery of data engineering and integration workstreams, guiding data engineers
- Operate and optimise the cloud data platform and related services
- Apply best practices in data engineering, automation, DevOps and platform operations
- Contribute to technical standards, patterns and documentation across the data engineering function
- Explain designs, risks and issues to technical and non-technical stakeholders to support engagement
- Deputise for the Head of Data Engineering on technical matters when needed
Key requirements
- Master in Computer Science, Data Engineering, Information Management or related discipline (or equivalent senior experience)
- Extensive knowledge of data engineering, cloud-based data platforms, integration and analytics enablement
- Post-qualification development in data engineering, cloud technologies, information governance or related digital disciplines
- Understanding of NHS digital policy and data strategy implications for platform delivery
- Aware of relationships among national NHS bodies, ICBs, providers and partners
- Desirable professional certifications (e.g., Azure Data Engineer, BCS, DAMA)
- Ability to communicate complex technical information clearly to diverse stakeholders
- Negotiation on technical and delivery issues
- Strategic thinking and problem-solving
- Microsoft Azure technologies
- Cloud-based data platforms
- Data pipelines and integration
Senior Data Engineer in Windsor employer: National Health Service
Betsi Cadwaladr University Health Board is an exceptional employer, offering a supportive and collaborative work environment for healthcare professionals in North Wales. With a commitment to employee development and a focus on compassionate care, staff have access to continuous professional development opportunities and the chance to make a meaningful impact in both acute and community paediatrics. The Health Board's integrated approach ensures that employees are part of a dynamic team dedicated to improving health outcomes for the local population.
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We think this is how you could land Senior Data Engineer in Windsor
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We think you need these skills to ace Senior Data Engineer in Windsor
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
