Role Overview – Senior Data Architect (Data & AI) Key Responsibilities• Govern and oversee the Enterprise Data Architecture framework supporting Data Analytics and AI initiatives across the organization.• Define and maintain conceptual, logical, and physical data models aligned with business, analytics, and AI requirements.• Review and validate data architecture designs, end-to-end data flows, data lineage, and integration patterns to ensure compliance with Data Governance, Data Quality, Security, and Privacy requirements.• Assess AI use cases from a technical architecture perspective, including data sourcing, integration, scalability, performance, and alignment with the target data architecture.• Establish and maintain technical controls supporting Responsible AI (RAI), including data validation, bias detection, explainability, traceability, and monitoring frameworks.• Review and evaluate vendor solutions to ensure alignment with enterprise architecture standards, integration capabilities, security requirements, and performance expectations.• Conduct data-focused assessments of third-party solutions, ensuring compliance with data protection, privacy, and regulatory requirements.• Review Business Requirement Specifications (BRS), solution designs, and Post-Implementation Reviews (PIR) from a data architecture perspective.• Govern data integration frameworks, ETL/ELT processes, APIs, streaming, and batch-based data flows across enterprise systems.• Support regulatory compliance initiatives, audits, and architecture governance forums.• Act as a Subject Matter Expert (SME) in Data Governance, AI Governance, Responsible AI, and Architecture Review forums. Required Skills and Experience• Minimum 7–10 years of experience in Data Architecture, Enterprise Data Management, Data Engineering, or related disciplines, preferably within banking or financial services.• Strong knowledge of enterprise data architecture principles, data modeling, data integration, and data governance frameworks.• Strong knowledge with modern data platforms, data warehouses, lakehouses, ETL/ELT frameworks, and analytics ecosystems.• Understanding of AI/ML data ecosystems, AI data requirements, and Responsible AI principles.• Experience reviewing architecture designs across on-premises, cloud, and hybrid environments.• Knowledge of Data Governance, Data Quality, Metadata Management, and regulatory data management requirements.• Strong analytical, architectural, and stakeholder management skills.• GCC and/or Qatar banking experience is highly desirable.• Professional certifications such as TOGAF, DAMA, CDMP, and Cloud Architecture certifications are preferred. Evaluation Criteria Submitted profiles will be assessed based on:• Relevance and depth of Data Architecture, Enterprise Data Management, and Data Engineering experience.• Experience in designing and governing enterprise-scale data platforms, architecture models, and integration frameworks.• Understanding of Data Governance, Data Quality, Metadata Management, Data Lineage, and architecture governance disciplines.• Exposure to AI/ML ecosystems, Responsible AI controls, and technical governance frameworks.• Banking / financial services domain exposure, preferably within Qatar or the GCC.• Ability to collaborate effectively across business, technology, risk, compliance, and governance stakeholders.• Availability to support immediate project timelines.