Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Strategy & Governance Lead

Grant Thornton UK
London
7 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Cloud Data Engineer

Cloud Data Engineer

Data Scientist

Data Scientist

More than you expected

Grant Thornton UK LLP is part of a global network of independent audit, tax and advisory firms, made up of some 73,000 people in over 150 countries. We're a team of independent thinkers who put quality, inclusion and integrity first. All around the world we bring a different experience to our clients. A better experience. One that delivers the expertise they need in a way that goes beyond. Personal, proactive, and agile. That's Grant Thornton.

Job Description:

NEW GROUND WON’T BREAK ITSELF.

Every day our teams help people in businesses and communities to do what is right and achieve their goals.

The Data Strategy & Governance Lead is a pivotal role within DRD (Data, RegTech and Digital) practice within FS BRS (Financial Business Risk Services). This role is responsible for providing specialized services in data management and data governance, and act as an SME on a wide range of client engagements including designing, and delivery of data standards across the organisations.

The role demands a proactive, self-motivated individual with strong communication skills and the ability to forge and maintain strong relationships. The successful candidate will be instrumental in growing the function and significantly contributing to business revenue and sales.

We’re happy to talk flexible working and consider reduced hours and job shares, we’ll support you to balance your work and life.

A look into the role

As a Data Strategy & Governance Lead within our Data, RegTech and Digital practice, you will:

  • Provide advisory services to clients including designing and implementing data governance frameworks.
  • Provide technical and practical advice and solutions tailored to individual client needs depending on the scale and nature of their business.
  • Define, assure and implement data and AI governance frameworks, including policies, standards, regulatory compliance, data risks and controls, data quality, metadata management, and regulatory compliance frameworks.
  • Implement and refine data management and governance tools to automate data management, enhancing efficiency and accuracy.
  • Drive sales and business development activities primarily within financial services industry, build and maintain strong client relationships, understand client needs, and develop tailored solutions that address those needs.

Knowing you’re right for us

Joining us as a Data Strategy & Governance Lead, the minimum criteria you’ll need is the ability to provide advisory services to clients including designing and implementing data management, data and AI governance frameworks, conduct data and AI maturity assessments, and benchmarking clients against industry best practices. Proven experience in data and AI strategy and data governance in Financial Services within a consultancy or industry. Experience in driving sales and business development activities. It would be great if you had some of the following skills, but don’t worry if you don’t tick every box, we’ll help you develop along the way.

  • A relevant data qualification e.g. CDMC, DAMA, DCAM.
  • Experience with data governance platforms and tools such as Collibra, Informatica, Alation, Ataccama or equivalent.
  • Experience with data software e.g. Snowflake, Databricks, Microsoft Purview, Collibra, Informatica or AWS.
  • In-depth knowledge of global data regulations and standards e.g., GDPR, DORA, BCBS 239, EU AI Act.
  • Thorough understanding of data architecture, data analytics and data management principles, and the ability to incorporate these into client solutions.

Knowing we’re right for you

Embracing uniqueness, the culture at Grant Thornton thrives on the contributions of all our people, we never settle for what is easy, we look beyond to deliver the right thing, for everyone. Building an inclusive culture, where we value difference and respect our colleagues helps our people to perform at the best of their ability and realise their potential.

Our open and accessible culture means you’ll interact with leaders who are interested in you and everything you bring to our firm. The things that set you apart, we value them. That’s why we give you the freedom to bring your whole self to work and pursue your passions inside and outside of work.

Beyond the job

Life is more than work. The things you do, and the people you’re with outside of work matter, that’s why we’re happy to look at flexible working options for all our roles, and we’ll always do our best to keep your work and life in balance.

The impact you can make here will go far beyond your day job. From secondments, to fundraising for local charities, or investing in entrepreneurs in the developing world, you’ll be giving back to society. It’s that drive to do the right thing that runs through our every move, grounded in our firm’s values – purposefully driven, actively curious and candid but kind.

We’re looking for people who want to contribute, spark fresh ideas and go beyond expectations. People who want to be able to proudly do what’s right, for the firm, our clients, our people and themselves.It’s how it should be.

#LI-ME1

#J-18808-Ljbffr

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.