Lead Data Analyst

Barclays
Glasgow
2 days ago
Create job alert

Step into the role of Lead Data Analyst at Barclays and play a pivotal part in shaping data-driven solutions across our banking platforms. In this role, you will bridge business needs and technical delivery, ensuring requirements are clearly defined, prioritized, and translated into high-quality solutions within an agile environment.

A strong understanding of banking domains—such as Core Banking, Onboarding, Payments, FX, Liquidity, and Cash Management—is essential. Experience working within or understanding data mesh concepts and “data as a product” principles will enable you to effectively collaborate across distributed data teams.

Desirably, you bring exposure to broader banking product stacks, including payments processing, core banking systems, ETL and reporting flows, and integrations using middleware technologies such as Kafka, MQ, or file-based patterns. Technical awareness is key, including proficiency in SQL, data interpretation, understanding of data models and system interfaces, and the ability to support defect triage and test cycles.

To be successful as a Lead Data Analyst, you should have:

  • Strong Requirements Engineering & Agile Analysis: Eliciting, validating and documenting BRDs/FRDs/user stories, Backlog refinement, feature mapping, supporting testing, Working within Agile frameworks
  • Domain Expertise in any banking stack: Core Banking, Onboarding, Payments, FX, Liquidity and Cash Management etc. Having worked in a data mesh world or understanding concepts around data as a product.
  • Agile Ceremonies & SAFe Program Events: Strong proficiency in writing epics, capabilities, features, and user stories with acceptance criteria that meet Definition of Ready/Definition of Done.

Other highly valued skills include:

  • Exposure to Broader Banking Product Stacks: Payment’s domain deep dive, Core banking systems, ETL / reporting flows, Integration with middleware (Kafka, MQ, file-based patterns).
  • Technical Awareness & Analytical Tools: SQL/data interpretation, understanding of data models, interfaces and system behaviour, Ability to support issue triage (defects, test cycles).
  • Risk Management & Regulatory Awareness: Risk & Controls, Regulatory Reporting, Liquidity Risk.

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 based in Glasgow with a hybrid working model of working a minimum of 2 days per week in the office.

Purpose of the role

To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.

Accountabilities
  • Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement
  • Designing and building data pipelines to automate data movement and processing.
  • Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI.
  • Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements.
  • Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs.
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 elevate 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.


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Analyst

Lead Data Analyst

Lead Data Analyst

Lead Data Analyst

Lead Data Analyst

Lead Data Analyst

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 Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.