Assistant Vice President – Loyalty Marketing (UAE Nationals)

About the role

The Assistant Vice President – Loyalty Marketing will lead the design and execution of loyalty marketing strategies for Aldar’s priority verticals in the UAE. Reporting to senior leadership, the role is responsible for driving revenue growth, profit and market share through data‑driven campaigns and lifecycle programs. The position is open exclusively to UAE nationals.

Key responsibilities

• Own marketing strategy and execution for selected priority verticals, ensuring deep alignment and measurable commercial outcomes.
• Manage the loyalty marketing P&L, including budget planning, allocation and financial forecasting.
• Evaluate and prioritize initiatives based on ROI, business impact and strategic alignment.
• Develop and deliver multi‑channel integrated loyalty campaigns in partnership with key stakeholders.
• Conceptualize and execute strategic loyalty points offers using data analytics to optimise acquisition, activation and retention.
• Drive higher activation rates and incremental revenue through refined lifecycle marketing programmes.
• Lead paid‑media and digital performance marketing across search, social, display, programmatic and app channels.
• Ensure compliance with legal, regulatory and data‑privacy requirements and work with operations to safeguard program integrity.

Required profile

• Minimum 8 years of experience in loyalty, customer‑lifecycle or strategic marketing, preferably in real‑estate or retail.
• Bachelor’s degree in Marketing or Business Administration.
• Strong leadership with proven ability to build cross‑functional relationships and influence consensus.
• Track record of delivering growth and positive ROI at both program and campaign levels.
• Deep understanding of business objectives, advanced analytics and the ability to translate insights into actionable plans.

Required skills

• Google Ads
• Meta advertising platforms
• Programmatic advertising platforms
• CRM / CDP environments
• Marketing attribution modelling
• Audience segmentation