Data Architect

Overview

The Data Architect will play a pivotal role in defining and evolving scalable data models and governance approaches for a leading UK Government Agency. This remote position involves collaboration with data, security, architecture, engineering, and business teams to ensure secure and well-managed data-sharing solutions. The successful candidate will be tasked with establishing a comprehensive understanding of data throughout its lifecycle, as well as translating complex technical concepts for various stakeholders.

Responsibilities

  • Define and deliver data architecture, data modeling and data governance activities.
  • Develop conceptual, logical and physical data models covering entities, attributes, relationships and dependencies.
  • Define and maintain data schemas, attributes, classifications, taxonomies and controlled vocabularies.
  • Map and document data lineage and provenance, including sources, transformations, dependencies and consumers.
  • Design scalable data structures supporting secure and interoperable data-sharing solutions.
  • Support the design of policy-based access control (PBAC) using appropriate data attributes and classifications.
  • Ensure data architecture supports auditability, traceability, regulatory and compliance requirements.
  • Contribute to data governance frameworks, standards, principles and processes.

Requirements

  • Proven experience as a Data Architect with expertise in data architecture and modeling within Agile environments.
  • Familiarity with Attribute-Based Access Control (ABAC) or Policy-Based Access Control (PBAC).
  • Strong understanding of data structures, schemas, entities, attributes, and relationships.
  • Experience with metadata management, data catalogues, and data lineage.
  • Ability to communicate complex data concepts to both technical and non-technical stakeholders.
  • Knowledge of data quality frameworks, validation, and compliance requirements.
  • Experience with APIs, data contracts and optimizing data models and integrations.
  • Understanding of the data lifecycle including creation, transformation, sharing, and retention.