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- Tasks: Lead a team to ensure data quality and governance in a dynamic financial services environment.
- Company: Join a leading Financial Services organisation driving a major data transformation.
- Benefits: Enjoy a competitive salary of £95,000, strong benefits, and flexible working options.
- Other info: Opportunity for hands-on leadership in a fast-paced, innovative environment.
- Why this job: Make a real impact on data quality and governance while collaborating with talented teams.
- Qualifications: Proven experience in Data Quality, Governance, and modern data engineering practices.
The predicted salary is between 95000 - 95000 £ per year.
A leading Financial Services organisation undergoing a large scale data transformation is looking to hire an experienced Data Quality Manager. The role offers a salary of £95,000 plus a strong benefits package and flexible working.
This role will suit a technically credible Data Quality leader with a genuine passion for data quality, accuracy and trust. You will work closely with data engineers and platform teams to embed pragmatic governance and quality controls into delivery, while influencing stakeholders across the business and possess a commercial mindset.
This is a hands-on technical leadership role, combining data quality and governance ownership with practical engineering input. You will lead a small team and partner with data engineers and operational SMEs to embed best practice across data quality, governance and data management.
- Own and evolve the data governance framework within an engineering-led environment
- Define governance standards, guardrails, data contracts and SLAs
- Partner with Risk, Audit, Data Protection and Legal to meet compliance requirements
- Work with data engineering teams to embed data quality into pipelines and workflows
- Provide hands-on guidance on data modelling, reconciliation, metadata and best practice
- Strong background in Data Quality, Data Governance and Data Management within a modern data engineering environment
- Hands-on experience with cloud data platforms, Azure, SQL, Python and orchestration tools
- Proven experience embedding data quality controls across data pipelines and ETL transformation workflows
- Good understanding of modern data architectures and quality control patterns
- Experience with data profiling, lineage analysis, reconciliation and metadata management
Data Quality Manager (Permanent) in London employer: McCabe & Barton
Contact Detail:
McCabe & Barton Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Quality Manager (Permanent) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the hunt for a Data Quality Manager role. You never know who might have the inside scoop on openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! When you get the chance to chat with potential employers, be ready to discuss your hands-on experience with data quality and governance. Share specific examples of how you've embedded quality controls in past projects – this will make you stand out!
✨Tip Number 3
Prepare for interviews by brushing up on the latest trends in data management and governance. Familiarise yourself with tools like Azure, SQL, and Python, and be ready to discuss how you've used them in real-world scenarios. This shows you're not just book-smart but also practical!
✨Tip Number 4
Don't forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace Data Quality Manager (Permanent) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Quality Manager role. Highlight your experience with data governance, quality controls, and any hands-on technical skills you have. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for data quality and how you can contribute to our team. Be sure to mention specific experiences that demonstrate your leadership and technical skills.
Showcase Your Technical Skills: Since this role involves hands-on technical leadership, don’t forget to showcase your experience with cloud platforms like Azure, SQL, and Python. We love seeing practical examples of how you've embedded data quality into workflows!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Good luck!
How to prepare for a job interview at McCabe & Barton
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of data quality, governance, and management. Be prepared to discuss specific examples from your past experience where you've successfully implemented data quality controls or improved data accuracy. This will show your technical credibility and genuine passion for the role.
✨Showcase Your Leadership Skills
As a Data Quality Manager, you'll be leading a small team. Think about how you've influenced stakeholders in previous roles and be ready to share those stories. Highlight your hands-on leadership style and how you’ve partnered with data engineers and operational SMEs to embed best practices.
✨Familiarise Yourself with Compliance Requirements
Since this role involves working with Risk, Audit, Data Protection, and Legal teams, it’s crucial to understand compliance requirements. Brush up on relevant regulations and be prepared to discuss how you've ensured compliance in your previous roles, especially in relation to data governance frameworks.
✨Demonstrate Your Technical Skills
Be ready to dive into the technical aspects of the role. Familiarise yourself with cloud data platforms like Azure, SQL, and Python. Prepare to discuss your hands-on experience with data pipelines, ETL workflows, and any orchestration tools you've used. This will help you stand out as a technically credible candidate.