Process Data Modelling Analyst

Overview

Purpose of the role: 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.

Role location:
Northampton.

• Investigate and analyse data issues related to quality, lineage, controls, and authoritative source identification; document data sources, methodologies, and quality findings with recommendations for improvement.
• Design and build 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; translate insights into actionable business recommendations driving operational and process improvements (leveraging machine learning/AI).
• Translate analytical findings into actionable business recommendations that identify opportunities for operational and process improvements.
• Design and create interactive dashboards and visual reports using applicable tools; automate reporting processes for regular and ad-hoc stakeholder needs.
• Contribute to the Enterprise Process data modelling capability for the Catalyst programme; support the design, documentation, and maintenance of Process Domain data models for reporting, analytics, and operational processes.
• Design, create, and support service wrappers around existing tooling, including integrations between systems; translate business requirements into conceptual, logical, and physical data structures while maintaining data quality, standards, and documentation.
• Collaborate with senior colleagues and stakeholders to define data requirements and ensure alignment with business objectives.

• Advise and influence decision making; contribute to policy development and operational effectiveness; collaborate with other functions and business divisions.
• Lead a team performing complex tasks (if applicable), setting objectives and coaching employees toward those objectives; assess performance and determine rewards where leadership responsibilities exist.
• Demonstrate Barclays Values (Respect, Integrity, Service, Excellence, Stewardship) and Barclays Mindset (Empower, Challenge, Drive).

• Data, analytics, information management, or database-related experience (internships, placements, graduate roles, or junior analyst positions).
• Experience with data modelling concepts (entities, relationships, keys, normalisation) and understanding of conceptual, logical, and physical data models.
• Exposure to process modelling tools and methods (e.g., BPMN-based tooling such as IBM Blueworks Live).
• Strong analytical thinking with the ability to break down business problems into structured data requirements; attention to detail in development, testing, and release of solutions.
• Experience with SQL and relational databases; ability to query, inspect, and validate data structures.
• Experience working with ETL tools; ability to document requirements clearly and work independently with stakeholders.
• Good written and verbal communication skills; ability to document clearly and work with multiple stakeholders.
• Other valued skills: data modelling or metadata tools (e.g., ERwin, ER/Studio, Power Designer); experience using REST APIs for integrations; familiarity with data warehousing, data governance, metadata management, data quality, and related initiatives.
• Degree in Computer Science, Information Systems, Data Science, Mathematics, Statistics, or related discipline, or relevant experience; familiarity with structured delivery environments (e.g., Agile).
• Evidence of risk and control, change and transformation, business acumen, strategic thinking, and digital/technological skills relevant to the role.