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.
