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

Apply Now

Data Quality and Governance Manager

Barclays Bank Plc
Manchester
3 days ago
Create job alert

As a Data Quality and Governance Manager you will be part of the Data Governance and Quality Team, you'll play a key role in safeguarding our customers' data and ensuring it's used responsibly across BUK. This involves identifying the root causes of issues and leveraging data to resolve customer challenges. You'll also support data governance processes and assist in managing our critical data elements


Please read the information in this job post thoroughly to understand exactly what is expected of potential candidates.

 

To be successful as a Data Quality and Governance Manager, you should have experience with

  • Proven experience using data and insights to address customer challenges

  • Great problem-solving skills with a focus on data-driven solutions

  • Knowledge of data governance, risk management, or controls

 

Some other highly valued skills may include

  • Experience working in an Agile environment

  • Proficiency in data analytics

  • Understanding of data privacy principles

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role can be based in Manchester (4PP), Glasgow or Northampton.


Purpose of the role

To develop, implement, and maintain effective governance frameworks for all data and records across the bank's global operations. 

Accountabilities

  • Development and maintenance of a comprehensive data and records governance framework aligned with regulatory requirements and industry standards.
  • Monitoring data quality and records metrics and compliance with standards across the organization.
  • Identification and addressing of data and records management risks and gaps.
  • Development and implementation of a records management programme that ensures the proper identification, classification, storage, retention, retrieval and disposal of records.
  • Development and implementation of a data governance strategy that aligns with the bank's overall data management strategy and business objectives.
  • Provision of Group wide guidance and training on Data and Records Management standard requirements.

Assistant Vice President Expectations

  • To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
  • Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
  • If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
  • OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
  • Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
  • Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
  • Take ownership for managing risk and strengthening controls in relation to the work done.
  • Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
  • Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
  • Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
  • Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
  • Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Related Jobs

View all jobs

Data Quality and Governance Manager

Data Quality and Governance Manager

Data Quality and Governance Manager

Data Quality and Governance Manager...

Data Quality and Governance Manager...

Data Quality and Governance Manager...

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.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.