Manager - Big Data & Platforms

Job Purpose :Lead the design, operation, and continuous development of RTA's enterprise data lake, data warehouse, and AI/ML platform infrastructure within the Big Data & Platforms section. Establish and enforce data governance, quality controls, and metadata management frameworks that ensure scalable, secure, and high-performance data services for artificial intelligence and analytics solutions. Driv the end-to-end data lifecycle—from ingestion and transformation to delivery—supporting model retraining, decision-making dashboards, and institutional data-driven excellence.

Roles and Responsibilities

StrategyLead the development and governance of RTA's corporate data registry and catalog for AI and analytics, encompassing data sources, ownership, classification, access conditions, and permitted use cases in coordination with relevant organizational units.Oversee the strategic design and evolution of the enterprise data lake, data warehouse, and AI/ML platform architecture to meet scalability, availability, resilience, and performance requirements aligned with RTA's digital transformation roadmap.Drive the implementation of data governance policies and operational controls in alignment with national data regulations, UAE data protection laws, and RTA's institutional data strategy.Manage and define the enterprise data quality framework, including issue tracking, remediation processes, and periodic reporting mechanisms to enhance data fitness for AI, analytics, and strategic decision support.Ensure proactive updates to data requirements needed for retraining smart models or introducing new variables in coordination with AI and analytics teams.Operations:Manage and define enterprise data models, databases, and metadata structures to support consistent, secure, and effective data utilization across RTA's business units.Lead build and maintain data ingestion and transformation pipelines, APIs, and data flows across approved sources, including scheduling, monitoring, error handling, and performance management.Provision and maintain updated datasets to support AI solutions, model retraining, dashboards, and analytics, defining refresh schedules and data service-level requirements.Manage, develop enterprise dashboards and analytical applications supporting decision-making, including product ownership, data definitions, user requirements, and full lifecycle management.Manage platform access permissions, licensing, and entitlements across all data and AI platforms in accordance with RTA's security and access control policies.Oversee backup, business continuity, disaster recovery, and vendor management services for enterprise data and AI platforms in accordance with approved operational controls.Provide technical and engineering support to development, operations, and authorized user teams manage incidents, service requests, corrective actions, and continuous improvement in coordination with relevant organizational units.Provision and configure AI platforms, data services, integration capabilities, and approved datasets for development and operations teams, coordinating with IT Management on shared core infrastructure. ensure define and enforce delivery and handover mechanisms with development and operations teams for platform, data, and integration requirements across solution development phases and production transitions.Product/Process Improvementoversee establish continuous improvement mechanisms to enhance data accuracy, platform effectiveness, and AI model readiness across the enterprise data ecosystem.Ensure strengthen data quality assurance processes and streamline data management workflows in collaboration with operational entities and data owners.Drive innovation in data platform capabilities, exploring and piloting emerging technologies for agentic AI systems, autonomous data processing, and advanced analytics.Ensure optimize data exchange mechanisms with external partners and government entities under approved data sharing agreements, ensuring compliance and value realization.Ensure conduct periodic feasibility studies and impact assessments for new data platform capabilities, integration requirements, and AI infrastructure enhancements.

Qualifications

Education: Bachelor, Master's degree in Computer Science, Data Science, Information Technology, Artificial Intelligence, or a closely related field from an accredited universityExperience:12+ years of progressive professional experience in case of Master degree (14+ years in case of Bachelor's degree)Qualification:Proven expertise in big data technologies (Hadoop, Spark, Databricks, cloud-native data platforms), enterprise data modeling, ETL/ELT pipeline design, API development, and metadata management