كبير مهندسي بيانات المؤسسات (Senior Enterprise Data Architect)

Job Summary

The Senior Enterprise Data Architect will design and implement scalable, governed data architectures to support AI, analytics, and data-driven decision-making across the organization. This role requires extensive experience in data architecture and related fields to translate business needs into secure and high-performing data platforms.

Responsibilities

• Define and implement enterprise strategies for AI, data, analytics, and information management.
• Create long-term roadmaps for data architecture, AI adoption, analytics, governance, and digital transformation.
• Lead the design, deployment, and management of enterprise data platforms and AI solutions.
• Develop scalable architectures for data lakes, warehouses, integration platforms, BI environments, and machine learning systems.
• Establish and improve enterprise data governance frameworks, policies, standards, and operating models.
• Enhance data quality, availability, security, privacy, lineage, ownership, and usability.
• Build organizational capabilities to promote data literacy and responsible AI use.
• Lead and optimize AI, data, analytics, and architecture teams and advise executive leadership on strategy and investments.

Must haves

• Bachelor’s degree in Computer Engineering, Computer Science, Information Systems, Data Science, or related field.
• Over 20 years of progressive experience in data architecture, engineering, AI, analytics, or enterprise architecture.
• Extensive expertise in enterprise data architecture, governance, management, warehousing, and business intelligence.
• Proven leadership in enterprise-scale transformation programs.
• Strong background in designing and implementing data warehouses, lakes, integration solutions, and analytics platforms.
• Experience developing and implementing AI and machine learning strategies.

Nice to haves

• Master’s degree in a relevant technical or business discipline.
• Professional certifications in enterprise architecture, data management, cloud, AI, analytics, or governance.
• Experience with cloud data platforms, modern data architectures, machine learning platforms, and advanced analytics.
• Knowledge of responsible AI, AI risk management, privacy, cybersecurity, and regulatory compliance.

We refresh listings regularly, but some roles close early on the source platform.