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# Data Analyst Modeller

- **Company:** Neweasy
- **Location:** London, UK
- **Salary:** £130,000.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Software as a Service, Data Governance, Data Profiling, Data Sharing, Data Structures, Entity Relationship Models, Python (Programming Language), Logical Data Models, Elearning, SQL Databases, Systems Integration, Data Strategy, Event Driven Architecture, Data Management
- **Published:** September 24, 2026
- **Apply:** https://www.reed.co.uk/jobs/data-analyst-modeller/57386517

## About the Role

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.

Applicants must already have unrestricted right to work in the UK. Visa sponsorship is not available for this opportunity.

## Description

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