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- Tasks: Design and build data pipelines while ensuring top-notch data quality.
- Company: Join University College London Hospitals' innovative SAFEHR team.
- Benefits: Competitive salary, professional growth, and a collaborative work environment.
- Other info: Exciting opportunities for career advancement in a dynamic healthcare setting.
- Why this job: Transform advanced research into real-world applications and contribute to open-source software.
- Qualifications: Experience in data engineering and a passion for collaboration.
The predicted salary is between 58133 - 65261 £ per year.
University College London Hospitals seeks a Data Engineer (AI Enablement) to join the SAFEHR team. This role involves designing and building data pipelines, developing a data warehouse, and ensuring data quality. You will work directly with clinicians and researchers to transform advanced research into real-world applications, contributing to open-source software. The position offers a salary of £58,133 – £65,261 and opportunities for professional growth in a collaborative environment.
Data Engineer, AI Enablement for Clinical Data in London employer: Society of Research Software Engineering
Contact Detail:
Society of Research Software Engineering Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer, AI Enablement for Clinical Data in London
✨Tip Number 1
Network like a pro! Reach out to current employees at University College London Hospitals on LinkedIn. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a mini-project or a portfolio showcasing your data pipeline designs and data warehouse development. This hands-on evidence can really impress during interviews.
✨Tip Number 3
Practice makes perfect! Get together with friends or fellow job seekers and do mock interviews. Focus on common questions for data engineers, especially around AI and clinical data.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have insider tips and updates on the hiring process that can help you stand out.
We think you need these skills to ace Data Engineer, AI Enablement for Clinical Data in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and AI. We want to see how your skills align with the role, so don’t be shy about showcasing your projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how you can contribute to the SAFEHR team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills: Since this role involves designing data pipelines and ensuring data quality, make sure to mention specific tools and technologies you’ve worked with. We’re keen to know how you can bring your expertise to our team!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Society of Research Software Engineering
✨Know Your Data Pipelines
Make sure you can discuss your experience with designing and building data pipelines in detail. Be ready to explain the tools and technologies you've used, as well as any challenges you faced and how you overcame them.
✨Showcase Your Collaboration Skills
Since you'll be working directly with clinicians and researchers, it's crucial to demonstrate your ability to collaborate effectively. Prepare examples of past projects where teamwork was key, and highlight how you communicated complex data concepts to non-technical stakeholders.
✨Emphasise Data Quality Assurance
Data quality is a big part of this role, so be prepared to discuss your approach to ensuring data integrity. Talk about specific methods or frameworks you've implemented in previous roles to maintain high standards of data quality.
✨Be Ready for Technical Questions
Expect technical questions related to data warehousing and AI enablement. Brush up on relevant concepts and be prepared to solve problems on the spot. Practising coding challenges or case studies can help you feel more confident during the interview.