Vice President – Data Platforms

AI in this role

ml-ops

JOB PURPOSE

Own the data backbone of the Group: the platforms through which data is ingested, stored, modeled, governed and made available for analytics, Artificial Intelligence and operational use across Aldar and its subsidiaries. Establish end-to-end accountability from data platform engineering to operations, building AI-ready foundations and a self-service model that lets Group Digital and the business consume trusted data at speed, without the data platform becoming a bottleneck. Serve Group Digital's Data & AI teams with data and self-service capabilities; analytics and data science ownership remains with Group Digital.

ROLES AND RESPONSIBILITIES

Data Platform Strategy & Architecture:

Define and evolve the Group data platform architecture: ingestion, storage, modeling, processing and serving layers. Design for reuse, scalability, security-by-design and cost efficiency across the Group and subsidiaries. Build AI-ready foundations: pipelines, data products and platform capabilities that support advanced analytics and Artificial Intelligence use cases.

Data Engineering & Ingestion:

Own data ingestion from enterprise and subsidiary source systems into the Group data platform, with reliable, monitored pipelines. Set engineering standards for data pipelines, data products and platform automation. Ensure database management and storage planning support performance and growth.

Platform Data Governance & Quality:

Implement platform-level data governance: data principles, cataloguing, lineage, quality monitoring and access controls. Safeguard master data alignment and data reliability for downstream consumers. Partner with Information Security on data protection controls across the platform.

Serving Group Digital & Self-Service:

Serve Group Digital's Data & AI teams with data and self-service capabilities, with clear interfaces and service commitments. Enable governed self-service for business and subsidiary teams, balancing autonomy with control. Provide centralized observability of data flows supporting digital products.

Operations & Reliability:

Ensure availability, performance and cost discipline of the data platform in production. Establish monitoring, incident management and capacity planning for data services. Drive FinOps discipline on data platform and storage spend.

Leadership & Talent Development:

Build and lead the Data Platforms team, including data platform and database management capabilities. Develop data engineering depth and support Emiratization objectives.

What This Role Is Not:

Not an analytics or data science role; those capabilities are owned by Group Digital. Not a reporting or Business Intelligence delivery function; the role provides the platform others build on. Not limited to Aldar corporate; the platform serves the Group and its subsidiaries. This role owns the data backbone on which the Group's analytics and Artificial Intelligence ambitions are built.

RELATED YEAR OF EXPERIENCE

Minimum of 10-12+ years in data platform engineering or data architecture leadership within large, complex organizations.

YOE IN MANAGERIAL POSITION

Minimum of 2+ years of managerial experience in a related field.

FIELD OF EXPERIENCE

Enterprise data platforms at group or multi-entity scale, including cloud data stacks Data engineering practices, data governance tooling and self-service enablement Building AI-ready data foundations (pipelines, MLOps-adjacent capabilities) is an advantage

TECHNICAL AND INTERPERSONAL SKILLS

Engineering leader with architectural depth; credible with both engineers and executive stakeholders Service mindset toward Group Digital and the business: the platform exists to be consumed Rigorous on data reliability, governance and cost discipline Comfortable operating at the boundary between technology platforms and digital product teams

QUALIFICATION

Bachelor's degree in a relevant field is required Master's degree is preferable

How we rate this

Vice President – Data Platforms at Aldar rates 69 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML Ops

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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