Manager-Data Platform Program Delivery

Job Description

• Enterprise Platform Delivery & Operations Leadership

• Own enterprise delivery and operational governance across multiple data platforms.
• Lead production readiness, hypercare governance, release management, operational acceptance, and transition into managed services.
• Govern enterprise platform lifecycle management including environment management, deployment governance, rollback planning, and operational stabilization.
• Ensure delivery alignment with strategic business objectives, roadmap priorities, operational timelines, and release schedules.
• Drive operational scalability, resiliency, observability, monitoring, and continuous service improvement initiatives.

• DataOps, MLOps & AI Operations

• Establish and scale enterprise-grade DataOps, MLOps, CI/CD, and AI operations frameworks.
• Define operational standards for model deployment, monitoring, retraining coordination, drift management, inference operations, and AI governance controls.
• Govern AI operational readiness and support processes for enterprise AI use cases across multiple production platforms.
• Standardize release management, deployment automation, testing governance, and operational quality assurance processes.

• Managed Services & Service Offering Development

• Design and scale enterprise Data & AI managed services offerings covering platform operations, application support, DataOps, MLOps, and AI operations.
• Develop reusable operational frameworks, governance standards, support models, delivery playbooks, and service catalogs.
• Define L1/L2/L3 support operating models, escalation procedures, SLA structures, and operational KPIs.
• Drive continuous improvement initiatives to enhance service quality, operational maturity, and delivery efficiency.

• Program Management & Delivery Governance

• Lead delivery execution across multiple Data & AI workstreams including data engineering, analytics, governance, AI enablement, and operational support.
• Monitor delivery progress, operational risks, issues, dependencies, and readiness activities across all programs.
• Ensure compliance with enterprise standards, governance policies, cybersecurity requirements, and operational controls.
• Govern delivery reporting, performance tracking, financial oversight, and operational accountability.

• Stakeholder Leadership & Client Engagement

• Act as the senior onsite engagement lead for Data & AI programs and operations.
• Build trusted relationships with executive stakeholders, sector leadership, technical teams, and implementation partners.
• Lead executive governance forums, steering committees, operational reviews, and strategic planning sessions.
• Drive alignment across business, architecture, operations, AI, infrastructure, and governance stakeholders.

• Vendor & Multi-Partner Governance

• Govern multi-vendor delivery and operational coordination across implementation partners, cloud providers, platform vendors, and support teams.
• Manage dependencies, escalation management, operational coordination, and delivery alignment across all involved parties.

• Capability Building, Staffing & People Management

• Define the long-term capability model required for sustainable enterprise Data & AI operations.
• Lead workforce planning, staffing strategy, onboarding, capability development, and succession planning.
• Support recruitment and management of Data & AI delivery, operations, governance, engineering, AI, PMO, and support resources.
• Coach and mentor teams to establish high-performance delivery and operational practices.

• Business Growth & Commercial Support

• Identify service expansion and upsell opportunities aligned with client strategic priorities.
• Support development of proposals, business cases, effort estimates, pricing models, and service expansion strategies.
• Manage delivery financials including forecasting, utilization tracking, operational efficiency, and margin optimization.

• Communication & Executive Reporting

• Provide executive-level dashboards, operational updates, release readiness reports, risk registers, and performance reporting.
• Lead communication planning and change management activities supporting operational adoption and stakeholder engagement.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Management, Artificial Intelligence, Engineering, Business Administration, or a related field.
• 12+ years of experience in enterprise Data & AI delivery, platform operations, managed services, or digital transformation programs.
• Proven experience leading enterprise scale DataOps, MLOps, AI operations, or Data & AI platform support organizations.
• Experience managing production critical enterprise platforms and large scale release programs.
• Experience establishing managed services, operational governance models, and scalable support capabilities from inception.
• Experience managing executive stakeholder relationships within government or large enterprise environments is highly preferred.

Technical Competencies

• Strong understanding of DataOps, MLOps, CI/CD, enterprise data platforms, data architecture, data governance, metadata, lineage, data quality, and analytics ecosystems.
• Experience operationalizing enterprise AI use cases in production environments.
• Strong understanding of AI/ML operationalization including model deployment, monitoring, retraining cycles, drift detection, inference operations, and AI governance controls.
• Familiarity with operational processes including testing governance, deployment pipelines, incident management, problem management, and service operations.

Leadership & Management Competencies

• Excellent executive stakeholder management, communication, negotiation, and leadership skills.
• Demonstrated experience leading multi-disciplinary teams across delivery, operations, AI, engineering, governance, and support functions.
• Strong strategic thinking and operational leadership capabilities.
• Ability to operate effectively in complex, multi-stakeholder, and multi-vendor environments.

Mandatory Requirements

• Fluent in English communication skills required, Arabic language fluency is very much preferred.
• Willingness to work onsite and lead client-facing engagement activities.