Role: Data Architect

The Role

Work closely with business and technology stakeholders to understand enterprise-wide data needs, define future-state data capabilities, and guide change. Develop, integrate, and govern enterprise data models, ensuring alignment across products, platforms, and business domains.

Influence organisational data strategy, contribute to data standards and governance, and ensure data architecture supports business outcomes with resilience, scalability, and regulatory integrity.

Requirements

Key Responsibilities

• Develop and maintain enterprise-level conceptual, logical, and physical data models.
  

• Define and evolve enterprise data architecture standards, principles, patterns, and best practices.
  

• Lead and facilitate workshops with stakeholders to define data requirements and align strategic initiatives.
  

• Ensure data models across products and platforms align with enterprise models and escalate variances where required.
  

• Work with product teams, business analysts, and solution architects to develop integrated, end-to-end data flows and enterprise conceptual frameworks.
  

• Maintain enterprise data dictionaries, taxonomies, and metadata repositories.
  

• Perform oversight and quality assurance on data architecture artefacts.
  

• Support the development of data governance frameworks and ensure that enterprise data standards are consistently adopted.
  

• Conduct reverse engineering and analysis of data structures across databases, SaaS platforms, and legacy systems to understand the enterprise landscape.
  

• Collaborate with domain and product data architects to ensure new data concepts are integrated into the enterprise architecture.
  

• Support operational teams with analysis on data-related production issues and root-cause investigations.
  

• Contribute to organisational capability by supporting communities of practice and wider technical forums.
  

• Provide data architecture input into enterprise and solution architecture to ensure consistent, predictable outcomes across programmes and projects.
  

Skills & Experience

• Hands-on experience in enterprise-level conceptual, logical, and physical data modelling in a complex organisation.
  

• Strong communication skills, with the ability to engage effectively with both technical and non-technical senior stakeholders.
  

• Experience with a range of modelling approaches (3NF, star schema, snowflake, Data Vault 2.0, etc.).
  

• Experience working with internal stakeholders to shape data use cases and deliver models aligned to organisational needs.
  

Essential Skills & Experience

• Proficiency with traditional data modelling techniques (IDEF1x, IE) and tooling such as Erwin, Solidatus (Data Lineage), Safyr, ABACUS, or Archi.
  

• Experience creating and maintaining enterprise data dictionaries, taxonomies, and metadata standards.
  

• Strong analytical and problem-solving skills with both logical and lateral thinking capability.
  

• Experience in business analysis, strategic requirements elicitation, and framing complex data challenges.
  

• Solid understanding of the Software Delivery Lifecycle (both Agile and Waterfall).
  

• Strong grounding in relational, dimensional, and enterprise modelling concepts.
  

• Awareness of enterprise-scale data warehousing, integration, and big data environments.
  

• Knowledge of cloud-based data architectures and big data technologies.
  

• Familiarity with Software Engineering principles and data-centric development approaches.
  

• Experience with SQL and/or other programming languages.
  

• Understanding of data analytics platforms, APIs, and database technologies.
  

• Experience using UML for class and domain modelling.
  

• Awareness of non-functional design elements (security, scalability, availability, performance).