SAP Master Data Governance Manager - MDG

Accenture UK & Ireland
London
2 months ago
Applications closed

Related Jobs

View all jobs

SAP Master Data Analyst

Senior Business Intelligence Manager

Senior Business Intelligence Manager

Senior Business Intelligence Manager

Data Analyst

Purchasing Data Quality Support Assistant

Role: SAP Master Data Governance Manager - MDG

Location: London /Birmingham/ Manchester

Salary: Competitive salary and package dependent on experience

Career Level: Manager

Accenture is a leading global professional services company, providing a broad variety of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge.

We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too.

“Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO

As a team:

As one of SAP’s Tier 1 global partners we understand the importance of data in our client’s transformation journeys. Whether in the context of a S/4HANA transformation or of a data roadmap we strive to bring leading thinking and delivery of innovative solutions to our clients. You will work on full lifecycle data journeys with clients from roadmap through to execution, delivering value through the latest features and benefits within SAP solution set.

In our team you will:


Advising clients on their data transformation strategies driving value creation through the positioning of SAP enabled solutions as well as leading solutions from SAP partners and Accenture.
Leading the data migration stream of an S/4HANA transformation, working with colleagues in delivery centres to execute on their data transformation strategies.
Work with a wide range of clients across many industries on their transformational journeys, ranging from smaller single function, in country projects to S/4HANA enabled global business transformations.


As a SAP MDG Manager you will:

Be an integral part of our team supporting our clients SAP transformation projects through acting as a Functional Expert in the master data governance area. You will work closely with clients, translating their business and functional requirements into SAP functional designs and overseeing solution delivery. Your strong business process knowledge, combined with your in-depth expertise will be key to designing effective and efficient solutions for our clients.

We are looking for experience in the following skills:


Experience of both advising clients on their Master Data Management strategy elements of their S/4HANA roadmaps and supporting the implementation of solutions based on SAP MDG and other complimentary MDM applications.
Leading the transformation of clients data governance models, ensuring the relevant business accountabilities are in place and a clear target operating model for MDM is implemented prior to the deployment of SAP MDG based solutions.
At least 7 years of functional data experience and recognised SME skills for at least two “Big 4” data objects demonstrated across multiple full E2E SAP implementation lifecycles from data strategy definition through to cutover.
Proven capabilities in leading a distributed delivery team, working with colleagues in offshore delivery centres for solution delivery.
Proven ability of advising & supporting clients with data quality challenges, working with the client to define corrective actions and deliver data quality monitoring solutions.
Understanding of methodologies for the deployment of SAP MDG.
Good understanding of Agile and Waterfall methodologies.


Set yourself apart:


Broader S/4HANA functional experience ensuring stronger alignment of SAP MDG with other functional solution elements.
Broader understanding of full data lifecycle management processes, especially instances where lifecycle stages are linked to non-SAP solutions.
Experience demonstrated in the development of solid relationships with client C-Suite stakeholders.
Experience of other leading MDM tools (e.g. SimpleMDG) that typically complement SAP landscapes.


What’s In It For You

At Accenture in addition to a competitive basic salary, you will also have an extensive benefits package which includes 30 days’ vacation per year, private medical insurance and 3 extra days leave per year for charitable work of your choice!

Flexibility and mobility are required to deliver this role as there will be requirements to spend time onsite with our clients and partners to enable delivery of the first-class services we are known for.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.