Lead Data Architecture📣 إعلان

About the Lead Data Architecture Role

Masdr is seeking a Lead Data Architecture to join its team in Riyadh. This full-time position focuses on leading and governing the enterprise data architecture landscape to support the organization's digital data and business solutions. Masdr provides integrated digital solutions to public and private sector organizations, aiming to enhance operational efficiency, customer experience, and data-driven decision-making through advanced digital technologies.

Role Purpose and Scope

The Lead Data Architecture will be responsible for ensuring the design and implementation of scalable, secure, and governed data platforms. These platforms are crucial for supporting analytics, data products, AI initiatives, and the overall enterprise data strategy. The role involves driving data architecture standards, integration frameworks, data governance practices, and continuous improvement to ensure reliable, high-quality data capabilities across Masdr.

Key Responsibilities

• Define, maintain, and govern enterprise data architecture principles, standards, frameworks, and best practices.
• Own enterprise data models, data domains, architecture standards, and reference architectures.
• Design scalable, observable, secure, and cost-efficient data architecture patterns for ingestion, storage, processing, and access.
• Ensure data architecture aligns with enterprise technology strategy, cybersecurity, data governance policies, and regulatory obligations.
• Lead architecture reviews and provide expert guidance on data initiatives, platform enhancements, integrations, and modernization.
• Establish and maintain architecture decision logs, reference models, lineage artifacts, and data lifecycle management practices.
• Define and govern data integration standards, exchange models, and data-as-a-product principles.
• Design architecture patterns that embed security, access control, auditability, lineage, and compliance by default.
• Ensure data platforms effectively support operational, analytical, AI/ML, and business intelligence workloads.
• Translate analytics, AI, and data monetization requirements into future-state data architecture and platform capabilities.
• Guide the evolution of the enterprise data platform roadmap with clear technical and business justification.
• Evaluate emerging technologies and recommend architectural improvements.
• Drive continuous improvement initiatives across data architecture, governance, integration, and platform capabilities.
• Establish architecture governance processes, quality controls, and performance standards.
• Identify data architecture risks, technical gaps, and optimization opportunities.
• Promote architecture best practices, standards adoption, and operational efficiency.
• Support the implementation of data lifecycle management, observability, and performance optimization practices.
• Collaborate with business leaders, product teams, engineering teams, analytics teams, and technology stakeholders.
• Act as a trusted advisor on enterprise data architecture, data governance, data platforms, and modernization initiatives.
• Partner closely with Data Engineering, Analytics, AI, and Product teams.
• Facilitate alignment between enterprise architecture, cybersecurity, infrastructure, and data management functions.
• Support cross-functional collaboration to drive data-driven transformation initiatives.
• Mentor and develop data architects, engineers, and data professionals.
• Drive knowledge-sharing initiatives and contribute to the growth of the organization’s data architecture capabilities.
• Stay informed about emerging trends, technologies, and industry best practices in data architecture, cloud data platforms, analytics, and AI.

Qualifications and Experience

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Minimum 5–6 years of experience in Data Architecture and Data Engineering.
• Strong expertise in scalable data platform design, data modeling, data integration, and data governance frameworks.
• Strong understanding of enterprise data architecture principles, data governance frameworks, and data management best practices.
• Experience designing and implementing modern data platforms, data lakes, data warehouses, and data integration solutions.
• Knowledge of cloud data technologies, analytics platforms, AI/ML data requirements, and enterprise data ecosystems.
• Experience establishing data standards, architecture governance processes, and data lifecycle management practices.
• Familiarity with cybersecurity principles, regulatory compliance requirements, metadata management, and data lineage concepts.
• Experience working with technology vendors, cloud providers, and data platform partners.
• Strong analytical, problem-solving, stakeholder management, communication, and leadership capabilities.