MDM Manager

Reading
1 month ago
Applications closed

Related Jobs

View all jobs

Data Governance Manager

Data Governance Manager

Data Systems Executive

Data Governance Manager

SAP Master Data Governance (MDG) Associate Manager

SAP Master Data Governance (MDG) Associate Manager

Master Data Manager

£80,000 - £85,000 (+car allowance: £5,800, bonus, pension, private health care)

Mentmore are working with a leading household name to secure a Master Data Manager.

Acting as a senior expert in MDM content, processes, and procedures.
Overseeing the establishment of a golden master record for all data assets, ensuring a single source of truth.
Advocating for and implementing MDM best practices.
Developing and implementing the MDM strategy and framework.
Setting up MDM processes to support data governance and stewardship.
Leading the implementation of business rules, overseeing data governance activities, and managing MDM data mapping and ingestion, ensuring the system aligns with the organization's data strategy.
Ensuring the quality of data in the enterprise data platform, implementing data governance practices, data validation processes, and other measures to ensure data accuracy and consistency.
Maintaining data quality and uniformity across diverse systems.
Addressing and resolving issues related to conflicting data ownership, data and rule definition, and data availability.
Implementing business rules and data governance activities within the MDM system.

Team Management

Demonstrated expertise in leading a Master Data Management team, providing guidance and support, and ensuring the achievement of team objectives. This includes fostering a collaborative environment, mentoring team members, and driving continuous improvement in master data management practices.

Aligning with Business Objectives

Ensure MDM solutions support the organization's business objectives, working closely with the Head of Data Management and Governance and other stakeholders.
Leading Master Data Projects: Partner with IT and business stakeholders to lead complex, cross-functional master data projects.
Collaborating with IT and Business Teams: Work closely with IT teams to oversee the implementation of the data solution, and with business teams to understand their data needs.
Implementing MDM Program: Activate and enforce the master data management program vision, promote the role of MDM, ensure adoption, and monitor and manage data quality within the MDM program, working with data owners and stewards to address any issues

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.