Data and AI Architect (Saudi Arabia)

Position Overview

We are seeking a seasoned and visionary Data and AI Architect to lead the design, governance, and optimization of our enterprise data architecture while integrating cutting-edge Artificial Intelligence (AI), Machine Learning (ML), and MLOps capabilities. This pivotal role will shape the organization’s data-driven future by ensuring that enterprise data assets are secure, governed, and leveraged to drive advanced analytics, scalable AI solutions, and informed decision-making across all business functions. The ideal candidate will combine deep technical expertise with strategic leadership to align data architecture with business objectives, fostering innovation and operational excellence.

Key Responsibilities

• Enterprise Data Architecture Leadership: Define and govern the organization’s enterprise data architecture, extending it to support AI, ML, and MLOps initiatives. Ensure alignment with business goals while maintaining scalability, security, and compliance.
• AI and ML Integration: Design and implement enterprise-scale AI and ML architectures, including generative AI solutions, to enable advanced analytics and automation. Collaborate with cross-functional teams to integrate AI capabilities into existing systems and processes.
• Data Governance and Quality: Establish and enforce enterprise data standards, governance frameworks, and technology roadmaps. Oversee master data management (MDM), metadata management, and data quality initiatives to ensure data integrity and reliability.
• Cloud-Native Data Platforms: Develop and optimize cloud-native data platforms, including data lakes, data warehouses, and lakehouse architectures. Leverage cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform to build scalable, high-performance solutions.
• Enterprise Integration and APIs: Design and implement enterprise integration technologies, APIs, and event-driven architectures to facilitate seamless data flow and interoperability across systems and applications.
• Security, Privacy, and Compliance: Ensure that data architecture adheres to security best practices, privacy regulations, and compliance requirements. Implement DevSecOps and CI/CD pipelines to integrate security and AI governance into the development lifecycle.
• Stakeholder Engagement and Leadership: Act as a trusted advisor to senior leadership, translating complex technical concepts into actionable business strategies. Foster collaboration across teams to drive adoption of data and AI initiatives and ensure alignment with organizational objectives.
• Technology Roadmap Development: Create and maintain enterprise architecture roadmaps that prioritize data and AI investments, balancing innovation with operational efficiency and risk management.

Qualifications and Experience

Education:

• Bachelor’s degree in Computer Engineering, Computer Science, Information Technology, Data Science, or a related field (required).
• Master’s degree in Data Science, Artificial Intelligence, Computer Science, or a related discipline (preferred).

Professional Experience:

• Minimum of 15 years of progressive experience in enterprise data architecture, data governance, and information management.
• Proven track record in designing enterprise-scale data platforms and integrating AI/ML capabilities into enterprise architectures.
• Experience establishing enterprise data standards, governance frameworks, and technology roadmaps.
• Hands-on expertise in AI/ML platforms, MLOps frameworks, and enterprise AI architectures.
• Strong understanding of enterprise integration technologies, APIs, event-driven architectures, and distributed data platforms.
• Familiarity with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
• Knowledge of enterprise architecture frameworks such as TOGAF and architecture governance practices.
• Exceptional stakeholder management, communication, and leadership skills.

Preferred Certifications:

• TOGAF Certification
• Microsoft Azure Solutions Architect Expert
• AWS Certified Solutions Architect – Professional
• Google Professional Cloud Architect
• DAMA Certified Data Management Professional (CDMP)
• Microsoft Azure AI Engineer Associate
• AWS Certified Machine Learning – Specialty

Technical Competencies

• Enterprise Data Architecture
• Data Governance & Data Quality
• Master Data Management (MDM)
• Metadata Management & Data Catalog
• Data Warehousing & Data Lakes
• Lakehouse Architecture
• AI & Generative AI Architecture
• Machine Learning & MLOps
• Enterprise Integration & APIs
• Security, Privacy & Compliance
• Analytics & Business Intelligence
• Architecture Governance
• DevSecOps & CI/CD for AI