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Process Data Modelling Analyst

Job in Northampton, Northamptonshire, NN1, England, UK
Listing for: 慨正橡扯
Full Time position
Listed on 2026-07-20
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineering, Business Systems & Technology Analysis, Data Warehousing
Salary/Wage Range or Industry Benchmark: 65000 - 90000 GBP Yearly GBP 65000.00 90000.00 YEAR
Job Description & How to Apply Below

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.
  • Experience of data modelling concepts, including entities, relationships, keys, normalisation, and the difference between conceptual, logical, and physical models.
  • Exposure to process modelling tools and methods, including IBM Blueworks Live or similar BPMN‑based tooling
  • 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 ETL 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:

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

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…
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