Senior Data Architect

Role Overview

The Senior Data Architect will oversee and govern the enterprise data architecture framework that supports data analytics and artificial intelligence initiatives across the organization. This role is responsible for defining and maintaining data models at conceptual, logical, and physical levels aligned with business, analytics, and AI needs. Key duties include reviewing data architecture designs and ensuring compliance with governance, quality, security, and privacy standards.

Key Responsibilities

• Manage and govern the enterprise-wide data architecture framework to support analytics and AI projects.
• Develop and maintain comprehensive data models that reflect the organization’s business and AI objectives.
• Validate data architecture designs, data flows, lineage, and integration to ensure compliance with data governance and security policies.
• Evaluate AI use cases technically focusing on data sourcing, integration, scalability, and alignment with the target architecture.
• Implement and uphold technical controls related to Responsible AI, including data validation, bias monitoring, explainability, traceability, and ongoing oversight.
• Review vendor solutions for alignment with enterprise standards, security, and performance criteria.
• Assess third-party data solutions to guarantee adherence to data protection, privacy, and regulatory standards.
• Analyze Business Requirement Specifications and solution designs from a data architecture viewpoint.
• Oversee data integration frameworks including ETL/ELT, APIs, streaming, and batch processing across various systems.
• Support compliance efforts, audits, and participate in architecture governance forums.
• Serve as a subject matter expert in data and AI governance as well as architecture reviews.

Required Skills and Experience

• 7 to 10 years of professional experience in data architecture, enterprise data management, or data engineering, ideally within banking or financial services sectors.
• Comprehensive knowledge of enterprise data architecture concepts, data modeling, integration, and governance frameworks.
• Familiarity with modern data platforms including data warehouses, lakehouses, ETL/ELT tools, and analytics environments.
• Understanding of AI/ML data ecosystems, AI data requirements, and principles of Responsible AI.
• Experience assessing architecture designs in on-premises, cloud, and hybrid infrastructures.
• Knowledge of data governance, quality assurance, metadata management, and adherence to regulatory data requirements.
• Strong analytical abilities combined with architectural insight and stakeholder management skills.
• Experience within GCC or Qatar banking industries is highly advantageous.
• Professional certifications such as TOGAF, DAMA, CDMP, or cloud architecture credentials are desirable.

Evaluation Criteria

• Candidates will be evaluated on the depth and relevance of experience in data architecture, enterprise data management, and data engineering.
• Expertise in designing and managing enterprise data platforms, architecture models, and integration processes.
• Knowledge of data governance, quality, metadata, lineage, and architecture control methods.
• Understanding of AI/ML ecosystem governance, including Responsible AI practices.
• Domain experience in banking or financial services, especially in Qatar or the GCC region.
• Ability to work collaboratively with stakeholders in business, technology, risk, compliance, and governance.
• Readiness to support immediate project deadlines.