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For Companies At a Glance
- Tasks: Lead the design and delivery of scalable data architecture and AI solutions.
- Company: Join a forward-thinking organisation in Edinburgh focused on impactful data and AI innovation.
- Benefits: Enjoy hybrid working, career development opportunities, and a supportive culture.
- Why this job: Make a real impact with cutting-edge technology in a strategic leadership role.
- Qualifications: Strong background in data engineering and AI, with leadership experience required.
- Other info: Work with tools like Azure AI and Power BI while mentoring a high-performing team.
The predicted salary is between 60000 - 68000 £ per year.
We’re Hiring: Lead AI and Data Engineer 📍 Edinburgh (Hybrid) | 💰 £60,000–£68,000
Are you passionate about AI, data engineering, and building systems that actually make an impact? We’re looking for a strategic and hands-on leader to shape the way our organisation leverages data and AI—from predictive models that drive real outcomes to scalable pipelines that power decision-making across the business. This is your chance to take the lead in a high-impact role where innovation, automation, and engineering excellence come together.
What You’ll Be Doing
- Design and deliver scalable data architecture, pipelines, and semantic models
- Build and deploy production-grade AI solutions (predictive & generative)
- Champion automation-first engineering and modern DataOps/MLOps practices
- Lead the development of AI & data products tied to measurable business outcomes
- Manage, mentor, and grow a high-performing data engineering team
- Work cross-functionally with architects, analysts, data scientists, and IT
- Use tools like Azure AI, Power BI, and open-source frameworks
- Stay ahead of the curve with GenAI and cloud advancements
What You Bring
- Strong background in data engineering and AI—with leadership experience
- Hands-on expertise in cloud-native (Azure) data and AI tools
- Deep understanding of modern data pipelines, APIs, and model deployment
- A passion for automation, continuous improvement, and scalable design
- Excellent communication and stakeholder engagement skills
- Ability to lead Agile development and manage structured deployments
Why Join Us?
- Strategic, high-ownership role at the heart of our data and AI strategy
- Supportive and forward-thinking culture
- Flexibility to innovate, lead, and make a visible impact
- Hybrid working and career development opportunities
Lead Data & AI Engineer employer: MBN Solutions
Contact Detail:
MBN Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data & AI Engineer
✨Tip Number 1
Network with professionals in the AI and data engineering fields. Attend industry meetups, webinars, or conferences to connect with potential colleagues and learn about the latest trends. This can help you gain insights into what we value at StudySmarter and how you can align your skills with our needs.
✨Tip Number 2
Showcase your hands-on experience with Azure and other relevant tools. If you've worked on projects involving cloud-native solutions or AI implementations, be ready to discuss these in detail. We appreciate candidates who can demonstrate their technical expertise and how it can benefit our team.
✨Tip Number 3
Prepare to discuss your leadership style and experiences. As a Lead Data & AI Engineer, you'll be managing a team, so think about examples where you've successfully mentored others or led projects. We want to see how you can inspire and grow our high-performing data engineering team.
✨Tip Number 4
Stay updated on the latest advancements in AI and data engineering. Familiarise yourself with emerging technologies and methodologies, especially in automation and DataOps/MLOps practices. This knowledge will not only impress us but also show your commitment to continuous improvement and innovation.
We think you need these skills to ace Lead Data & AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering and AI, particularly any leadership roles. Use specific examples that demonstrate your hands-on expertise with cloud-native tools like Azure.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data engineering. Discuss how your background aligns with the responsibilities of the role, especially your experience in building scalable data architectures and leading teams.
Showcase Relevant Projects: Include details about specific projects you've worked on that relate to predictive models, automation, or DataOps/MLOps practices. Highlight measurable outcomes to demonstrate your impact.
Prepare for Interviews: Anticipate questions related to your leadership style, technical skills, and experience with cross-functional collaboration. Be ready to discuss how you would approach the challenges outlined in the job description.
How to prepare for a job interview at MBN Solutions
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with cloud-native tools, especially Azure. Highlight specific projects where you've designed scalable data architectures or deployed AI solutions, as this will demonstrate your capability to meet the job's technical requirements.
✨Emphasise Leadership Skills
Since the role involves managing and mentoring a team, share examples of how you've successfully led teams in the past. Discuss your approach to fostering a high-performing environment and how you’ve contributed to team members' growth.
✨Demonstrate Your Passion for Innovation
Talk about your enthusiasm for automation and continuous improvement. Share any experiences where you've implemented modern DataOps/MLOps practices or innovative solutions that had a measurable impact on business outcomes.
✨Prepare for Cross-Functional Collaboration
The role requires working with various stakeholders, so be ready to discuss how you've effectively communicated and collaborated with different teams in previous roles. Highlight your ability to engage with architects, analysts, and data scientists to drive projects forward.
