Key Responsibilities
Define logical and physical data models, including NoSQL data structures, to support business and technical requirements.
Establish and maintain data structures, data flows, and end-to-end documentation across systems.
Define and document data requirements, inputs, outputs, and lineage using approved data lineage and traceability tools.
Lead the creation and maintenance of API documentation and data integration specifications.
Ensure data consistency, integrity, and quality across systems, aligning with governance frameworks and regulatory standards.
Implement and uphold data governance processes in collaboration with central data architecture and governance teams.
Contribute to broader architecture decisions to ensure adherence to organisational standards and technical strategy.
Support and oversee data-related testing activities by clarifying data models, flows, and requirements for testing teams.
Conduct impact analysis and support life cycle management of data assets, identifying opportunities for reuse and optimisation.
Engage with cross-functional stakeholders-including developers, testers, product and technical architects, senior leadership, and governance forums-to communicate design decisions and obtain approvals.
Provide guidance and oversight to data analysts and support other architects as required.
Ensure adherence to security, privacy, and compliance requirements, including meeting clearance requirements where applicable.
Skills Required
Strong experience in data architecture with proven expertise in data modelling for relational and NoSQL databases, covering structured and unstructured data.
Hands-on experience with cloud platforms, particularly AWS, and NoSQL technologies such as DynamoDB.
Strong understanding of system integrations, including API-based workflows, data exchange patterns, and integration documentation.
Proficiency in designing and managing data integration workflows across diverse platforms.
Experience with data lineage, metadata, and traceability tools (eg, Solidatus) or the ability to quickly adopt such tools.
Solid understanding of data governance principles, data quality processes, data life cycle management, and regulatory compliance.
Strong analytical and problem-solving skills with the ability to translate business requirements into effective data designs.
Excellent communication and stakeholder management skills, with experience engaging senior leadership, technical teams, and governance bodies.
Experience supporting data-focused testing activities and clarifying data models and flows for testing teams.
Ability to work effectively across multiple delivery teams in Agile environments and adapt to evolving project needs.