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For Companies At a Glance
- Tasks: Build and refactor data models, develop APIs, and enhance AI/ML functionality.
- Company: Leading upskilling platform in Greater London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Shape the future of data access and make a real impact in a dynamic environment.
- Qualifications: Expertise in cloud-native development and data engineering practices required.
- Other info: Join a collaborative team dedicated to evolving data architecture and security.
The predicted salary is between 48000 - 72000 £ per year.
A leading upskilling platform in Greater London is seeking a Senior Data Engineer to create the technical foundations for data access across the organization. You will build and refactor data models, develop APIs, and enable seamless AI/ML functionality within the Internal Developer Platform. This role requires expertise in cloud-native development and data engineering practices. The ideal candidate will also advocate for security and evolve the data architecture as the product matures, ensuring that all data operations are efficient and user-friendly.
Senior Data Engineer: Architect Self-Serve AI Data Platform employer: Multiverse
Contact Detail:
Multiverse Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer: Architect Self-Serve AI Data Platform
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Senior Data Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and APIs. We want to see your work in action, so don’t be shy about sharing your projects when you get the chance.
✨Tip Number 3
Prepare for those interviews! Brush up on cloud-native development and data engineering practices. We recommend practising common interview questions and even doing mock interviews with friends to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and take the initiative to connect directly with us.
We think you need these skills to ace Senior Data Engineer: Architect Self-Serve AI Data Platform
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with cloud-native development and data engineering practices. We want to see how your skills align with the role of a Senior Data Engineer, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about building data platforms and how you can contribute to our mission at StudySmarter. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills: In your application, make sure to highlight your expertise in developing APIs and evolving data architecture. We’re looking for someone who can advocate for security while ensuring data operations are efficient, so give us the details on your technical prowess!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Multiverse
✨Know Your Data Engineering Fundamentals
Brush up on your data engineering principles, especially around cloud-native development and data modelling. Be ready to discuss your experience with building and refactoring data models, as well as developing APIs. This will show that you understand the core responsibilities of the role.
✨Showcase Your AI/ML Knowledge
Since the role involves enabling AI/ML functionality, be prepared to talk about any relevant projects you've worked on. Highlight how you've integrated AI/ML into data platforms in the past, and be ready to discuss the challenges you faced and how you overcame them.
✨Emphasise Security Practices
Security is a big deal in data engineering. Make sure you can articulate your understanding of security best practices and how you've implemented them in previous roles. Discuss any frameworks or tools you’ve used to ensure data integrity and security.
✨Demonstrate Your Adaptability
The job requires evolving the data architecture as the product matures. Share examples of how you've adapted to changing requirements in past projects. This will show that you're not just a technical expert but also someone who can grow with the company and its needs.
