Data Architect at IQbusiness

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.