Lead- Partner Talent & Certifications

Lead- Partner Talent & Certifications will lead EXLs enterprise-wide partner talent and certification strategy across AI, Data, Cloud, Analytics, Engineering, and Agentic AI ecosystems. The role will build and scale partner-specialized talent aligned with market demand, client opportunities, delivery priorities, partner commitments, and future workforce requirements. The individual will serve as the central orchestration point across Capability Development, Technology Partnerships, business units, delivery leadership, and strategic technology partners. The role will directly contribute to talent readiness, partner status, funding realization, capability differentiation, and revenue enablement.

Key Responsibilities:

• Partner Talent Strategy: Define and execute EXLs enterprise partner talent strategy, translating market demand, growth priorities, and alliance commitments into multi-year capability and certification plans.
• Specialized Talent Supply: Build scalable pipelines of partner-specialized practitioners, engineers, consultants, architects, technical leaders, and GTM talent across priority technologies and proficiency levels.
• Demand-to-Skill Alignment: Work with business, sales, solution, and delivery leaders to forecast capability demand and align certification investments with client pursuits, project pipelines, solution roadmaps, and deployment needs.
• Partner Ecosystem Leadership: Act as the capability interface for strategic technology partners and maximize learning assets, vouchers, credits, bootcamps, funding, co-investment opportunities, badges, competencies, and partner-tier requirements.
• Certification Portfolio Management: Own the enterprise certification portfolio, including pathways, nominations, readiness interventions, exam governance, renewals, badge validation, partner-portal mapping, and active certification health.
• Capability Architecture: Create progressive pathways from foundation awareness to practitioner, advanced, architect, and specialist credentials, supported by academies, labs, assessments, mentoring, and applied learning.
• Enterprise Program Leadership: Lead certification campaigns, partner academies, acceleration cohorts, deep-dive sessions, hackathons, certification weeks, and targeted interventions across business units and geographies.
• Talent Deployment & Impact: Establish mechanisms to connect certified talent with client opportunities, delivery roles, internal gigs, solution development, and partner-led GTM motions.
• Governance & Executive Reporting: Lead cross-functional governance and provide executive visibility into readiness, demand-supply gaps, certification funnels, pass rates, costs, funding utilization, deployment, risks, and corrective actions.
• Team & Operating Model: Build a disciplined operating model, lead internal and external program resources, manage vendors, and create repeatable processes that can scale across partner ecosystems.

Technology Partner Ecosystems Understanding Required:

• Microsoft (Azure, Fabric, Copilot, and AI)
• 
  AWS
• Google Cloud
• Databricks
• Snowflake
• NVIDIA
• Anthropic (Claude)
• OpenAI
• Salesforce
• Genesys
• Palantir and other emerging strategic technology partners

Capability & Program Management Skills Required:

• Partner talent and certification strategy
• Certification portfolio and lifecycle management
• Enterprise program governance and PMO
• Partner funding, incentives, and benefit optimization
• Demand-supply and talent deployment planning
• Vendor, budget, and commercial management

Data & Analytics Skills Required:

• Advanced Excel and PowerPoint
• Power BI / Tableau
• Certification funnel, pass-rate, and renewal analysis
• Demand-supply and capability-gap analysis
• Dashboard design and executive reporting
• Data governance, reconciliation, and audit readiness

AI / Data / Cloud Knowledge Desired:

• Generative AI and Agentic AI
• Large Language Models and enterprise AI use cases
• Cloud platforms and modernization concepts
• Data engineering, analytics, and modern data platforms
• AI/ML, MLOps, and AI operations fundamentals
• Responsible AI, governance, security, and risk concepts
• Partner certification frameworks, competencies, and tiering models

Leadership & Soft Skills Desired:

• Strong executive presence and business communication
• Strategic thinking with commercial and talent acumen
• Ability to influence senior leaders and drive accountability without direct authority
• Strong partner relationship and negotiation skills
• Data-driven decision-making and structured problem solving
• Ability to lead complex enterprise programs in a global matrix
• High ownership, attention to detail, and execution discipline
• Strong people leadership, coaching, and team-development capability
• Ability to balance long-term strategy with hands-on operational execution

Qualifications:

• Bachelors degree in Engineering, Technology, Business, Human Resources, or a related discipline.
• 8-12 years of experience in technology enablement, capability development, partner management, learning strategy, workforce transformation, or a related field.
• Demonstrated experience building and scaling certification or specialized-talent programs in Data, AI, Cloud, Digital Engineering, technology consulting, or professional services.
• Experience working with global technology partners, business leaders, delivery organizations, and certification ecosystems.
• Relevant cloud, data, AI, program management, or partner certifications will be an advantage.