Job Description

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.

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.

Join us as a Process Data Modelling Analyst to help scale EPT data modelling capability for the Catalyst programme. Where you will contribute to the development of the Enterprise Process data model, bringing together logical and physical process taxonomies with Enterprise Journeys, business capabilities, and integrated risk and resilience management.

This role is responsible for supporting the design, documentation, and maintenance of Process Domain data models that enable consistent, accurate, and usable data for reporting, analytics, and operational processes associated with the Enterprise Process Taxonomy (EPT). The role includes the design, creation and support of service wrappers around existing tooling, including integrations between systems. The role will work with senior colleagues to translate business requirements into conceptual, logical, and physical data structures, while helping maintain data quality, standards, and documentation.

To be successful as a Process Data Modelling Analyst you must have the following experience:

• Data, analytics, information management, or database-related role, which may include internships, placements, graduate roles, or junior analyst positions.

• Basic understanding of data modelling concepts, including entities, relationships, keys, normalisation, and the difference between conceptual, logical, and physical models.

• Evidence of strong analytical thinking and the ability to break down business problems into structured data requirements:

  • Demonstrates attention to detail in the development, testing and release of solutions.

  • Exposure to SQL and relational databases, with the ability to query, inspect, and validate data structures.

  • Experience working with structured data in tools such as Excel, SQL-based platforms, or reporting/analysis tools.

  • Requirements documentation and clear communication, with the ability to work independently with stakeholders.

  • Good written and verbal communication skills, including the ability to document clearly and work with multiple stakeholders.

Other highly valued skills include:

• Exposure to process modelling tools and methods, including IBM Blueworks Live or BPMN-based tooling.

• Experience using a data modelling or metadata tool such as ER win, ER/Studio, PowerDesigner, or equivalent.

• Experience of using REST APIs to implement integrations between platforms:

  • Exposure to data warehousing, reporting data structures, data governance, metadata management, and data quality practices or supporting data migration, transformation, or systems change initiatives.

  • Degree in Computer Science, Information Systems, Data Science, Mathematics, Statistics, or a related discipline, or prior experience in this field.

  • Familiarity with structured delivery environments (e.g., Agile, project lifecycle).

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 Northampton.