Data Architect

Job Description

• Define and maintain fit-for-purpose data architecture for priority organisational systems and initiatives. Ensure business data concepts, models, flows, mappings and governance controls form a coherent, traceable design that supports current delivery and the target modern data architecture.
• Primary focus with be to Deliver governed, reusable and decision-ready data outcomes for priority systems and initiatives.

Key accountabilities

• Lead data architecture discovery for assigned systems, projects or domains; establish scope, assumptions, dependencies, constraints and decision points.
• Develop and govern conceptual, logical and physical data models at the level required by the initiative; align entities, definitions, keys, relationships and domains with enterprise standards.
• Design and review data flows and source-to-target mappings, including source, transformation, target, ownership, frequency, quality controls and lineage.
• Identify authoritative sources, master and reference data, critical data elements, data ownership and stewardship needs in collaboration with business and governance stakeholders.
• Define architecture patterns for ingestion, transformation, data layers, metadata, lineage, quality, access and data sharing; align designs to the federated platform direction and relevant security/privacy requirements.
• Maintain traceability between business requirements, data definitions, models, mappings, platform components and implementation decisions.
• Facilitate architecture reviews and approval packs; record decisions, exceptions, risks and remediation actions.
• Provide architectural guidance to engineers, modellers, analysts and process roles; review implementation designs and resolve cross-system data issues.

Core outputs

• Approved or review-ready CDM/LDM/PDM artefacts and modelling conventions.
• Data dictionaries, data flow diagrams, source-to-target mappings, master/reference data definitions and CRUD matrices as applicable.
• Data architecture views for domains, authoritative sources, integration, ingestion, processing, data layers, metadata, lineage and sharing.
• Architecture decision records, standards/patterns, review comments, risks, dependencies and sign-off evidence.
• Traceability and cross-tool references, including ARIS and SAP PowerDesigner identifiers where those tools are used.

Recommended qualifications and experience

• Degree or diploma in information systems, computer science, data management or a related discipline; equivalent experience may be accepted.
• TOGAF Certification is advantageus.
• Substantial experience in data architecture, data modelling or solution architecture in a complex enterprise environment.
• Experience with conceptual, logical and physical modelling and enterprise data artefacts; familiarity with SAP PowerDesigner and ARIS is advantageous.
• Experience with modern data platforms, integration patterns, metadata/catalogue, lineage, data quality and data governance.
• Working understanding of information security, privacy, access control and regulatory obligations relevant to enterprise data.

Knowledge and capabilities

• Enterprise and solution data architecture; domain modelling; relational and analytical data design.
• Data integration, ETL/ELT, APIs, batch and CDC concepts; data layer and lakehouse patterns.
• Data governance, ownership, stewardship, classification, quality, lineage and master/reference data.
• Architecture facilitation, visual communication, standards interpretation and decision documentation.
• Clear written communication and ability to explain technical trade-offs to business and governance audiences.
• Capable of compiling and presenting data architecture artefacts to the organisation's Enterprise Architecture Board for approval.

Key working relationships

• Enterprise Architecture and relevant approval boards; Data Governance and Data Management stakeholders.
• Business system owners, data owners, SMEs and data stewards.
• Data Engineers, Data Modellers, Data Business Analysts and Data Process Engineers.
• Project Office, BPM, information security, platform/cloud and integration teams.

Indicative performance measures

• Architecture deliverables are complete, internally consistent, traceable and accepted at agreed review gates.
• Models, mappings and data flows meet agreed standards and adequately reflect validated source/target realities.
• Architecture risks, dependencies and decisions are raised promptly and have clear owners and actions.
• Designs support agreed quality, security, privacy, lineage and interoperability requirements.
• Stakeholders can use approved artefacts to guide build, governance and future change.