Data Modeller​/Analytics Engineer

Job Summary

This is a rare opportunity to join a newly created global data modelling lead role, in a growing central data and analytics team. Your key work will be to lead the design and build of governed, reusable global data models that translate enterprise data into business‑ready dimensions, facts and metrics for consistent reporting, self‑service reporting, analytics and AI/ML readiness. You will be the bridge between the data team, IT leaders and business leaders: understanding and defining requirements, shaping data products, modelling business logic, and enabling performant, well‑documented accurate data delivery at a global scale.

This work relates predominantly in year one to corporate services data, specifically finance and human resources. You will be the global lead in RES for data modelling and analytics engineering, educating and training regional staff, providing templates and guidance on best practice. Lead working groups with the business/IT and define comprehensive business requirements from stakeholders. From the business requirements assess buy versus build options and if a data platform build is chosen then design the data model in conjunction with IT/data teams and business domain leaders.

Once signed off, build, deliver and maintain a comprehensive, scalable data model and lead implementation, optimisation, and scalability.

• Design global data models aligned to agreed business definitions, KPIs and reporting departments in conjunction with executives, business domains and senior IT leaders.
• Develop and maintain metric definitions and calculation logic to ensure model consistency across dashboards and reports.
• Build, deliver and maintain curated data modelling and products with documentation, tests, and versioning.
• Partner with data governance, architecture, system owners, business domains and cyber to align models to systems schemas, metadata management, business requirements, ownership, and certification/security.
• Optimise models for performance, quality and usability, ensuring scalable, future‑proof models are delivered.
• Collaborate with and lead work with Data Engineers/Architects on upstream transformations and data quality rules, ensuring end‑to‑end traceability, lineage and master data management. Collaborate with and lead/advise report developers and end users of the data (business/IT/data practitioners) to make effective use of the models.
• Support self‑service enablement: templates, guidance, and guardrails for analysts and report builders.
• Lead working groups and work with stakeholders to articulate business requirements and model development with IT and business domain leaders.
• Deliver complex, executive reports to educate and gain buy in and support for business requirements and global data model design.
• Lead programmes of work and ensure they are run effectively to time, quality standards and meeting budget requirements.
• Educate and train regional staff and provide templates and guidance on data modelling best practice, as the global lead for data modelling.
• Be able to lead and enable data modelling for AI/ML use cases by providing quality datasets and impactive data models and advise data scientists on engineering and modelling needs.

• Strong data modelling expertise: dimensional modelling, business rules, dimensions; data patterns.
• Ability to define and govern metrics and model consistency across multiple products and source system integrations.
• SQL mastery and experience with transformation frameworks and testing/documentation practices. SQL, building Star Schema data models and ETL & DAX.
• Deeply skilled in BI, including semantic layers (e.g., Power BI semantic models) and performance/cost optimisation.
• Extensive skills in data quality, traceability and observability integrated into modelling workflows.
• Strong stakeholder skills to translate business requirements into robust data products.
• Effective communicator with strong influencing, negotiating, and relationship‑building skills. Ability to articulate modelling to executives. Ability to translate complex data into meaningful insight for non‑technical audiences.
• Able to work independently, manage…