Manager - Big Data & Platforms

Job Purpose

Strategy

• Lead the corporate data registry and catalog, covering data sources, ownership, classification, access conditions, and permitted use cases.
• Oversee data lake, warehouse, and AI/ML platform architecture to meet scalability, availability, resilience, and performance needs.
• Implement governance policies and controls aligned with national data regulations, UAE data protection laws, and RTA's data strategy.
• Define data quality frameworks, issue remediation, and reporting; keep data requirements current for model retraining and new variables.

Operations

• Manage enterprise data models, databases, and metadata structures for secure, consistent use across business units.
• Lead ingestion and transformation pipelines, APIs, and data flows, including scheduling, monitoring, error handling, and performance.
• Provision datasets for AI solutions, model retraining, dashboards, and analytics, with refresh schedules and service-level requirements.
• Manage dashboards and analytical applications from product ownership and user requirements through lifecycle management.
• Manage data and AI platform permissions, licensing, and entitlements; oversee backup, continuity, disaster recovery, and vendors.
• Provide technical support, manage incidents and service requests, configure data and AI services, and coordinate platform delivery and handovers.

Product and Process Improvement

• Improve data accuracy, platform effectiveness, data quality assurance, and AI model readiness with operational entities and data owners.
• Explore and pilot capabilities for agentic AI, autonomous data processing, and advanced analytics.
• Optimize data exchange with external partners and government entities under approved sharing agreements.
• Conduct feasibility studies and impact assessments for platform capabilities, integrations, and AI infrastructure enhancements.

Qualifications

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