At a Glance
- Tasks: Lead a team in delivering AI and ML projects while mentoring engineers.
- Company: Global financial services leader with a focus on innovation.
- Benefits: Competitive salary up to £160,000 plus bonuses and hybrid work options.
- Other info: Opportunity for growth in a collaborative and agile environment.
- Why this job: Shape the future of AI/ML in a dynamic, impactful role.
- Qualifications: Strong background in AI/ML, data engineering, and leadership experience.
The predicted salary is between 160000 - 160000 £ per year.
A leading global financial services organisation are looking for a Director of Data Engineering with a focus on their AI & ML initiatives. You'll act as the technical lead and people manager for six engineers, owning end-to-end delivery across AI, machine learning, and data engineering initiatives. This is a mix of a hands-on and managerial position. You won't be running a large org; you'll be close to the work, setting the technical direction, and developing a high-performing team.
Key Responsibilities:- Leading a team of six AI/ML and data engineers, acting as the technical anchor and day-to-day people lead for the group
- Owning end-to-end delivery of AI, ML, and data platform initiatives within an agile POD structure
- Designing and scaling enterprise-grade data pipelines, ML systems, and MLOps capabilities
- Defining and communicating technical strategy, translating complex engineering decisions into clear narratives for senior stakeholders and business leaders
- Mentoring and developing engineers, fostering growth and technical excellence within the team
- Strong technical background in AI/ML and data engineering — you've built and shipped production ML systems and data platforms, not just overseen them
- Demonstrated ability to communicate and present to senior stakeholders with confidence and clarity — this is a significant focus for this hire
- Leadership experience — this doesn't have to mean large-team management; mentoring, tech lead roles, or small-team leadership is genuinely considered sufficient
- Experience in complex, enterprise-scale environments with real delivery accountability
- Experience in financial services, fintech, or similarly regulated industries (explicitly not required — strong candidates from any sector are welcome)
- Familiarity with MLOps, cloud-native data architectures, and enterprise data integration patterns
Director of Data Engineering (AI/ML) in Bolton employer: Burns Sheehan
Join a leading global financial services organisation in Manchester, where innovation meets opportunity. As a Director of Data Engineering, you'll thrive in a hybrid work environment that promotes collaboration and flexibility, while enjoying competitive compensation and a strong focus on employee development. With a culture that values mentorship and technical excellence, this role offers the chance to lead a talented team and make a significant impact in the AI and ML space.
StudySmarter Expert Advice🤫
We think this is how you could land Director of Data Engineering (AI/ML) in Bolton
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Burns Sheehan.
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We think you need these skills to ace Director of Data Engineering (AI/ML) in Bolton
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Burns Sheehan, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Burns Sheehan. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Burns Sheehan
✨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!
✨Showcase Your Projects
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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Burns Sheehan!
✨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.
