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For Companies At a Glance
- Tasks: Build and evolve a cutting-edge cloud agnostic data and AI platform.
- Company: A leading advisory firm focused on technology and innovation.
- Benefits: Competitive salary, learning opportunities, and influence on architectural decisions.
- Why this job: Make a real impact in regulated financial markets with innovative tech solutions.
- Qualifications: Strong Python skills, cloud engineering experience, and familiarity with AI tools.
- Other info: Dynamic team culture that values experimentation and career progression.
The predicted salary is between 48000 - 72000 £ per year.
A highly regarded advisory firm is investing heavily in its technology and innovation capability to support long term growth across data, analytics, and client facing digital products. This is not a support role and not a back office engineering position. You will work close to senior stakeholders, helping to design and deliver platforms that directly underpin revenue, insight, and differentiation in regulated financial markets.
What You Will Actually Be Working On
- Building and evolving a cloud agnostic data and AI platform using modern open source technologies
- Taking AI and GenAI solutions out of proof of concept and into secure, scalable production
- Developing and enhancing client facing digital products, dashboards, and AI driven insights
- Automating manual and inefficient processes using AI and RPA tooling
- Modernising legacy systems into resilient, API first architectures
- Embedding security, governance, and regulatory controls into platform design from day one
- Partnering with business leaders to turn data into commercial outcomes
Key experience includes
- Strong Python development with solid object oriented design
- Cloud and platform engineering using Kubernetes, serverless, CI CD, and infrastructure as code
- Data engineering concepts including ETL or ELT, streaming, metadata, and data quality
- Exposure to ML, GenAI, or MLOps in production environments
- Relational databases and SQL
- Experience working in regulated or security conscious environments is advantageous
- Hands on use of AI tools such as custom GPTs, chatbots, or workflow automation
What Sets This Apart
- Ownership over platforms, not just features
- Real influence on architectural and tooling decisions
- A team that values engineering judgement and long term thinking
- Broad exposure across cloud, data, AI, and client products
- A culture that backs learning, experimentation, and progression
Platform Data Engineer: AI, Cloud & Production employer: McGregor Boyall
Contact Detail:
McGregor Boyall Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Platform Data Engineer: AI, Cloud & Production
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving Python, cloud engineering, or AI solutions. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to data engineering and AI, and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who can help us innovate and grow. Your next big opportunity could be just a click away!
We think you need these skills to ace Platform Data Engineer: AI, Cloud & Production
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience with Python, cloud engineering, and any relevant AI projects. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our innovative projects. Keep it engaging and personal – we love a good story!
Showcase Relevant Projects: If you've worked on any cool projects involving AI, cloud platforms, or data engineering, make sure to mention them. We’re keen to see real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get the attention you deserve. Plus, it’s super easy!
How to prepare for a job interview at McGregor Boyall
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and understand object-oriented design principles. Be ready to discuss your experience with cloud technologies like Kubernetes and serverless architectures, as well as your familiarity with data engineering concepts like ETL or ELT.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've taken AI solutions from proof of concept to production. Highlight any experience you have in automating processes using AI and RPA tooling, and be ready to explain how you approached these challenges.
✨Understand the Business Impact
Since this role involves partnering with business leaders, think about how your technical work translates into commercial outcomes. Be prepared to discuss how you've turned data into actionable insights that drive revenue or improve client-facing products.
✨Emphasise Security and Compliance
Given the regulated nature of the environment, it's crucial to demonstrate your understanding of security, governance, and regulatory controls. Share any relevant experiences where you embedded these considerations into your platform designs from the outset.
