Data 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.
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 & 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.
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.
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.
Desired Candidate Profile
Education & Experience
Bachelor’s or Master’s degree in Computer Science, Information Systems, Business Administration, or a related field.
12+ years of experience in enterprise Data & AI delivery, platform operations, managed services, or digital transformation programs.
Experience managing production critical enterprise platforms.
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.
Ability to operate effectively in complex, multi-stakeholder, and multi-vendor environments.
Mandatory Requirements
Proven experience leading enterprise scale DataOps, MLOps, AI operations, or Data & AI platform support organizations.
Experience establishing managed services, operational governance models, and scalable support capabilities from inception.