Senior Manager, Enterprise Execution & Intelligence

Description

The Senior Manager, Enterprise Execution & Intelligence is responsible for building and leading the enterprise execution, governance, data, operational intelligence, vendor management, release enablement, and AI-readiness capabilities required to turn strategy into measurable business results. 

This role is responsible for establishing and managing the operating rhythms, standards, reporting, and decision-support systems that improve execution quality, accountability, visibility, and cross-functional alignment across enterprise initiatives. Key management areas include PMO discipline, Transaction Intelligence foundations, enterprise data governance, operational intelligence, release governance, vendor governance, business reporting, and cross-functional technical project execution. 

The Senior Manager, Enterprise Execution & Intelligence partners closely with Product Delivery leaders, Principal Engineers, Infrastructure & Engineering, Product Support Analysts, Data Engineering, Release & Enablement, Vendor Governance, Technical Project Management, Security, Operations, and executive stakeholders to create scalable organizational capability. 

Responsibilities and Duties

• Own the Enterprise Execution & Intelligence operating model by translating strategy into scalable execution systems, governance mechanisms, performance visibility, operating routines, and measurable business outcomes across Product Delivery, Infrastructure & Engineering, and enterprise initiatives. 
• Lead Transaction Intelligence and enterprise data-governance initiatives by partnering with Data Engineering, Product Delivery, business stakeholders, and executive leadership to establish trusted data foundations, KPI frameworks, information architecture, data quality practices, and future AI-ready data capabilities. 
• Establish and mature enterprise PMO capabilities, portfolio visibility, project governance standards, prioritization routines, status reporting, risk management, dependency tracking, and execution disciplines that improve initiative success and organizational accountability. 
• Provide leadership and governance oversight for enterprise technical initiatives, operational improvements, transformation programs, and physical product engineering projects through partnership with the Technical Project Manager, Infrastructure & Engineering, Product Delivery, Operations, vendors, and business stakeholders. 
• Lead enterprise vendor-governance practices, including performance management, service-pricing governance, SLA accountability, scorecards, contract-value realization, renewal planning, escalation management, and strategic third-party oversight. 
• Provide organizational leadership for Product Support Analysts and operational-intelligence functions by ensuring incident trends, problem records, defect origination, product reliability signals, severity patterns, and customer-impacting issues are translated into actionable business insights and continuous improvement opportunities. 
• Oversee release-governance, enablement, knowledge-management, and readiness functions by partnering with the Release & Enablement Manager to improve launch quality, documentation standards, internal enablement, organizational readiness, product-knowledge quality, and AI-ready knowledge foundations. 
• Partner with the AI Steering Committee, Product Delivery leadership, Infrastructure & Engineering, Security, Data Engineering, and business stakeholders to advance AI enablement, governance readiness, responsible-use practices, enterprise adoption priorities, and future AI capability maturity. 
• Develop and maintain enterprise performance measures, governance reviews, executive dashboards, portfolio reporting, operating reviews, and decision-support processes that provide leadership with timely visibility into strategy execution, risk, performance, and organizational effectiveness. 
• Build, lead, coach, and develop a high-performing Enterprise Execution & Intelligence organization while fostering a culture of accountability, operational excellence, continuous improvement, data-driven decision-making, cross-functional partnership, and measurable business value. 
• Performs other related duties as assigned to support the organization’s goals and objectives.

Requirements

• Bachelor’s Degree in Business Administration, Engineering, Information Technology, Computer Science, Data Analytics, Management Information Systems, Operations, or related field, or equivalent experience required. 
• 7+ years of progressive leadership experience in technology, data, product delivery, enterprise transformation, PMO, software delivery, operations, consulting, vendor governance, or related discipline required. 
• 5+ years of direct people-leadership experience managing cross-functional teams, enterprise programs, operational functions, technical organizations, governance functions, or strategic initiatives required. 
• Demonstrated experience building and scaling enterprise governance, PMO practices, operational frameworks, portfolio-management disciplines, reporting structures, or cross-functional execution models required. 
• Experience leading enterprise-wide initiatives involving data strategy, analytics, business intelligence, data governance, digital transformation, AI enablement, process improvement, technical project management, or organizational change required. 
• Strong business and financial acumen with experience developing business cases, prioritizing investments, evaluating ROI, managing budgets, improving vendor value, and aligning technology initiatives with business outcomes required. 
• Demonstrated ability to influence executive leadership, product organizations, engineering teams, operational stakeholders, technical teams, external partners, and cross-functional business leaders without relying solely on direct authority required. 
• Experience with portfolio management, project management, operational reporting, analytics, knowledge management, release governance, vendor governance, Microsoft 365, Power BI, Jira, Confluence, AI-enabled productivity tools, or similar enterprise platforms preferred.