Manager – Data Analytics | Emirati Talent – Majid Al Futtaim

This Manager – Data Analytics role, designated for Emirati Talent, sits within Majid Al Futtaim’s Data & AI function, contributing to a growth and innovation agenda the group has placed real strategic weight behind. The role is specifically focused on analytics quality, adoption, and value realization – making sure the analytics the business builds actually gets used and actually drives decisions, not just produced and shelved.

Day to day, this means overseeing standards for analytics quality and reproducibility, working with business stakeholders to drive genuine adoption of analytics tools and insights, and pushing continuous improvement across the analytics lifecycle from data to decision. Because Majid Al Futtaim operates across malls, retail, entertainment, and hospitality, this role likely touches analytics use cases spanning several of those businesses, which means working with a genuinely wide range of stakeholders with different levels of data fluency.

This is a role that requires both technical analytics credibility and the influencing skill to get often-skeptical business teams to actually change how they make decisions based on data.

This suits a UAE National analytics professional who wants to work on real adoption and value problems, not just model-building, within a group investing seriously in its Data & AI capability.

A business can invest heavily in data and analytics capability and still see little return if the analytics never actually changes how decisions get made - this role exists specifically to close that gap. By focusing on quality, adoption, and reproducibility rather than just producing more dashboards and models, this role protects the return on Majid Al Futtaim's broader Data & AI investment, making sure analytics work translates into genuinely better decisions across malls, retail, entertainment, and hospitality businesses. Poor analytics adoption is a common and expensive failure mode in large organizations - sophisticated models that nobody trusts or uses - and this role is the safeguard against that outcome. Strong work here compounds: each successful adoption builds more trust in data-driven decision-making across the group, making the next analytics initiative easier to land. That kind of consistency is easy to underrate from the outside, but it is precisely what the business is paying for when it fills a role like this one.

Analytics adoption and value realization is a distinct and increasingly valued specialization within the broader data and AI field - it sits closer to the business impact side of analytics than pure technical model-building, which makes it genuinely good preparation for analytics leadership or Chief Data Officer-adjacent career paths. Being part of Majid Al Futtaim's Data & AI growth agenda as Emirati Talent also means real visibility and investment from a group clearly serious about building this capability, including likely exposure to senior data and business leadership. The role builds a rare combination of technical analytics credibility and stakeholder influence skill that is in high demand as more organizations struggle with exactly the adoption problem this role addresses. For a UAE National analytics professional, this is a strong platform toward senior analytics, data strategy, or broader Data & AI leadership roles, both within Majid Al Futtaim and across the wider market. That foundation matters most in the long run, because the specific tools and systems in any given role tend to change, while strong fundamentals built early carry forward into whatever comes next. Just as importantly, it builds the day-to-day professional habits - clear communication, follow-through, and comfort being accountable for a defined piece of the business - that hiring managers look for regardless of which direction a career ends up taking next.

• UAE National status, in line with this role’s Emiratisation designation
• Bachelor’s degree in data science, statistics, computer science, or a related field
• Experience in data analytics, ideally including responsibility for analytics quality standards or adoption initiatives
• Strong understanding of the analytics lifecycle, from data quality through to business decision-making
• Ability to influence business stakeholders to adopt data-driven approaches, even where there’s initial skepticism
• Familiarity with analytics and BI tools, and an understanding of what reproducible, trustworthy analytics looks like
• Strong communication skills for translating technical analytics concepts into business language