Data Analyst Modeller

Key Responsibilities

• Develop and maintain logical data models across multiple products, platforms and business domains.
• Create and maintain entity relationship diagrams to clearly define entities, attributes and relationships.
• Analyse existing data sources across a complex, multi-system technology estate.
• Map data between existing systems and target models.
• Identify data quality issues, gaps, inconsistencies and conflicting definitions.
• Use SQL to interrogate, profile and validate source data.
• Understand how information flows between systems, applications and services.
• Support the definition of API and event-based data contracts.
• Define and document shared data concepts and common business terminology.
• Work within existing organisational taxonomy, data standards and governance frameworks.
• Collaborate with enterprise data specialists to ensure programme-level models align with wider organisational data strategy.
• Support the definition and evolution of canonical or golden records where appropriate.
• Work with product and engineering teams to understand locally owned data models and how they interact with the wider ecosystem.
• Facilitate workshops with subject-matter experts and business stakeholders to establish common definitions.
• Validate proposed data models with technical and non-technical stakeholders.
• Present models and recommendations through appropriate architecture and governance forums.
• Maintain data models, mappings, glossaries and supporting documentation as requirements evolve.

Essential Skills and Experience

• Strong commercial experience in data analysis and logical data modelling.
• Demonstrable experience developing conceptual and logical data models within complex, multi-system environments.
• Strong experience creating entity relationship diagrams.
• Strong SQL capability.
• Experience with data profiling and data quality analysis.
• Ability to identify entities, attributes, relationships and data boundaries across complex business domains.
• Experience mapping source data to target models.
• Understanding of APIs, system integration and data exchanged between applications.
• Understanding of event-driven architectures and modern integration patterns.
• Experience working with shared data definitions, business glossaries or taxonomies.
• Experience with master data, canonical records or golden record concepts.
• Experience using recognised data modelling tools.
• Strong stakeholder engagement and workshop facilitation skills.
• Proven ability to build consensus around definitions and data structures.
• Ability to communicate complex data concepts clearly to technical and non-technical audiences.
• Ability to work effectively within an evolving transformation environment

Desirable Experience

• Experience within SaaS or product-led technology environments.
• Experience within education technology, digital learning, assessment or similar digital services.
• Experience working across Azure and/or AWS environments.
• Python experience.
• Experience with graph or knowledge-graph modelling.
• Understanding of international data residency requirements.
• Exposure to AI-enabled products or technology environments

Candidate Profile

This opportunity is expected to suit a mid-to-senior-level data professional.

The successful candidate must be equally comfortable working with data and people.

Strong technical modelling capability is essential, but so is the ability to speak with subject-matter experts, understand real-world business concepts, challenge assumptions and gain agreement around proposed structures.