Senior Data Analyst Business Partner

Barclays
Glasgow
3 months ago
Applications closed

Related Jobs

View all jobs

Business / Data Analyst

Senior Data Analyst

Senior Data Analyst - Customer Data

Senior Data Analyst

Data Analyst - E-Commerce

Senior Data Analyst

As a Senior Data Analyst Business Partner at Barclays, you will be leading a team at the heart of ensuring the highest standards of data quality while working closely with business stakeholders to implement new data processes. Your primary focus will be improving data integrity, driving innovative data initiatives and ensuring that data systems are streamlined and effectively integrated across the business. In addition to your core responsibilities, you will play a key role in coaching and supporting junior members of the team, sharing your expertise to foster their development and ensure a strong, collaborative team environment.


To be successful as a Senior Data Analyst Business Partner, you should have experience with:



  • Proven experience in business and data analysis within a complex end-to-end architecture.
  • Expertise in re‑engineering and owning data and process operating models.
  • Demonstrated success in implementing new governance or operating models across large global teams or functions.

Other highly valued skills also include:



  • Senior‑level experience in data management, risk, and controls within a financial services organisation.
  • Certification in process improvement or Lean Six Sigma.
  • In‑depth knowledge of Risk, Finance, or Treasury business areas.

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 is hybrid and based in Glasgow.


Purpose of the role

To enable effective data governance, risk management, and compliance within the bank, acting as a liaison between business units and the Data & Records Management (DRM) function, translating business needs into actionable strategies and ensuring efficient implementation of DRM.


Accountabilities

  • Partnership with the local business unit to ensure successful implementation of data & records governance frameworks as appropriate to the needs of the business unit.
  • Provision of guidance and support on records classification, retention, storage, retrieval and disposal to business units.
  • Monitoring local data quality and records metrics and identify areas for improvement.
  • Identification of opportunities for data improvement and optimisation.
  • Partnership with the relevant business unit to support their data priorities and ensure appropriate decisions related to data & records are embedded in their BAU decision making and change programmes.

Vice President Expectations

  • To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures.
  • If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.
  • 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 be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi‑year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.
  • Advise key stakeholders, including functional leadership teams and senior management on functional and cross‑functional areas of impact and alignment.
  • Manage and mitigate risks through assessment, in support of the control and governance agenda.
  • Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
  • Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
  • Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
  • Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In‑depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
  • Adopt and include the outcomes of extensive research in problem solving processes.
  • Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills 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.



  • Demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship.
  • Display the Barclays Mindset – Empower, Challenge and Drive.
  • Show a moral compass in decision‑making.
  • Maintain a strong ethical standard in all work.
  • Promote a culture of continuous improvement and learning.


#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.

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.

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.

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.