Data Architect

Role Overview The expert will define the enterprise-wide data architecture for a complex, multi-entity organization. The role will translate business and data strategy into a coherent target architecture, common data models, integration patterns, platform capabilities, governance standards and a phased transition roadmap, while enabling interoperability across business units and entities. Key Responsibilities Assess the current data landscape across business units and entities, including data sources, platforms, models, flows, integrations, ownership, dependencies and key pain points. Define enterprise data architecture principles, standards and the target-state architecture across data ingestion, integration, storage, processing, sharing, analytics and AI enablement. Develop conceptual and logical enterprise data models, canonical models and common definitions for priority data domains. Define data-domain boundaries, data-product interfaces and interoperability standards for a federated, multi-entity environment. Establish architecture patterns for APIs, event-driven integration, batch exchange and secure data sharing across internal and external ecosystems. Advise on the architecture of data lakehouse or warehouse platforms, master and reference data, metadata catalogues, lineage, data quality, security and privacy controls. Align the data architecture with business capabilities, application architecture, technology strategy and enterprise-wide transformation priorities. Define data architecture governance, decision rights, design-review gates, reusable patterns and exception-management processes. Identify architecture gaps, dependencies and migration priorities, and develop a practical transition roadmap. Facilitate architecture workshops and translate complex technical decisions into clear recommendations for senior stakeholders.

15+ years of relevant experience in data architecture, enterprise information architecture, data engineering or large-scale data transformation. Proven experience defining enterprise-wide data architecture for a large, complex organization, conglomerate, public-sector ecosystem or other multi-entity environment. Strong expertise in conceptual and logical data modelling, enterprise data domains, canonical models and data interoperability. Deep understanding of modern data platforms, including cloud or hybrid data architectures, lakehouse or warehouse patterns, data integration and analytics ecosystems. Strong knowledge of data governance, metadata, lineage, master data management, data quality, security and privacy-by-design principles. Experience establishing federated architecture standards and aligning diverse business units and entities around common enterprise patterns. Ability to connect data architecture decisions to business outcomes, operating-model implications, investment requirements and implementation priorities, and communicate them clearly to senior stakeholders