Senior Director, Warehouse Management Systems & Labor Management Systems

- Define, own, and execute the enterprise technology strategy, roadmap, and lifecycle management for WMS and LMS platforms across McKesson's distribution network. - Maintain full end-to-end accountability - from strategy through execution - for platform availability, delivery performance, operational reliability, and financial outcomes. - Establish clear platform principles, guardrails, and success metrics that enable disciplined, outcome-driven decision-making across engineering and operations teams. - Align WMS and LMS strategy with distribution operations, supply chain priorities, and enterprise technology architecture to ensure investments deliver measurable business value.

- Drive a culture of delivery excellence - teams execute with speed, quality, and accountability in support of mission-critical distribution center operations. - Establish clear delivery standards, remove execution bottlenecks, and enable teams to ship outcomes faster while maintaining reliability and operational stability. - Own operational governance across distribution centers, ensuring Root Cause Analysis (RCA) and Corrective and Preventive Actions (CAPA) are delivered on time, clearly documented, and understood by both technical and non-technical leaders. - Define and track engineering KPIs that drive accountability and continuous improvement: - M anage portfolio of projects and reduce TCO - System availability and uptime - Incident reduction and mean time to resolution - Delivery predictability and cycle time - Code quality and technical debt reduction - Automation coverage and engineering productivity

- Champion the use of AI coding tools - GitHub Copilot, Claude Code, and emerging platforms - to measurably increase engineering speed, reduce analysis time, and improve code quality across WMS and LMS teams. - Model AI-first practices personally. Build a culture of experimentation where teams identify where AI helps, prove it with results, and scale what works. - Establish repeatable, teachable examples of AI-accelerated delivery - impact analysis, code review, RCA documentation, test case generation - and actively share these across the broader engineering organization. - Drive the expectation that AI adoption is a practice built through doing, not a training program.

Teams experiment, document results, and share learnings every sprint. - Partner with other engineering leaders to build a shared library of AI use cases that elevates productivity across the organization - not just within WMS and LMS.

- Lead modernization of legacy WMS and LMS ecosystems - cloud enablement, scalable architectures, modern integrations, and improved data and analytics capabilities. - Evaluate and recommend platforms, tools, and technologies that improve system reliability, developer productivity, and long-term sustainability. - Establish governance for platform replacement decisions that improve operational performance and total cost of ownership.

- Provide executive leadership for labor management capabilities that measure and improve workforce productivity across distribution centers. - Partner with Distribution Operations to ensure labor standards, reporting, and analytics support data-driven operational decisions.

- Own budgets and financial planning for WMS and LMS platforms - operating costs, capital investments, vendor contracts, and total cost of ownership. - Ensure every technology investment delivers measurable operational and financial value; articulate ROI clearly to senior business and finance leaders. - Identify and act on opportunities to reduce cost, consolidate platforms, and improve financial efficiency across the portfolio. - Accountability for relationship management for the Distribution team, managing escalations for any of the technological components

- Act as a strategic partner to Distribution Operations, Strategic Distribution & Automation, WCS/WES, Architecture, Cybersecurity, and Infrastructure teams.

- Maintain senior vendor relationships - roadmap alignment, contract oversight, and performance management for WMS and LMS partners and system integrators.

- Lead and develop a multi-layer organization of managers, engineers, analysts, and offshore teams. - Build a culture of accountability, ownership, operational excellence, and continuous improvement - where people are expected to grow, lead, and deliver. - Drive performance management, succession planning, and leadership development across the organization. - Recognize and amplify AI adoption and engineering innovation - build a team reputation for working differently and proving it with results.

Leadership Expectations : The successful candidate will demonstrate the following characteristics:

- Speed, Boldness & Innovation: Drives execution with urgency. Encourages bold ideas, challenges the status quo, and actively pushes teams to adopt AI and modern engineering practices. Does not wait for permission to move. - Operating in Ambiguity: Thrives where processes are still evolving.

Builds operating models and engineering practices from the ground up. Candidates seeking fully defined structures may not find this environment a fit. - Operational Ownership: Leads with full accountability for outcomes and system reliability in mission-critical environments. Sees what needs to be done and moves - without being asked. - Solution-Oriented Leadership: Builds a culture where teams bring solutions, tradeoffs, and execution plans.

Leaders here are decisive and drive clarity, not escalation. - Clear Business Communication: Communicates complex technical concepts clearly to senior leaders, operations, and engineers alike. RCA, incident reviews, and improvement plans are crisp, actionable, and audience-appropriate. - Building High-Performing Teams: Develops people, drives accountability, and builds a team culture where continuous improvement and AI adoption are the norm - not the exception.

Measures of Success - Success in this role will be measured by the following outcomes:

- Platform availability, uptime, and incident reduction targets met or exceeded across WMS and LMS systems. - Delivery predictability improved - teams ship on time, with quality, and with measurable reduction in production defects and escalations. - RCA and CAPA completion rates meet defined SLAs; findings are clear, actionable, and understood by non-technical leaders. - AI adoption is visible and measurable - specific examples of AI-accelerated delivery are documented, shared, and actively scaled across the engineering organization. - Modernization milestones achieved on schedule with clear operational and financial value demonstrated. - Strong, trusted partnerships with Distribution Operations and Supply Chain leadership - evidenced by timely decisions, reduced escalations, and positive stakeholder feedback. - Budget targets met; technology investments deliver defined operational and financial returns. - Leadership bench strengthened - direct reports are developing, performing, and ready for greater scope. - Team culture reflects accountability, speed, and continuous improvement - not escalation dependency.

- Bachelor's degree in Information Systems, Engineering, Supply Chain, or a related field (or equivalent experience). - 12+ years of progressive experience in warehouse, supply chain, or enterprise systems leadership. - 6+ years leading managers and senior technical or product teams. - Deep experience with Warehouse Management Systems in complex, high-volume distribution environments. - Demonstrated experience owning enterprise platforms with significant operational and financial impact.

- Experience with Labor Management Systems, engineered labor standards, or workforce productivity platforms. - Experience integrating WMS with WCS/WES and material handling automation in automated distribution centers. - Experience leading mission-critical operational systems where downtime directly impacts warehouses, logistics, or manufacturing. - Demonstrated AI adoption in engineering environments - using tools like GitHub Copilot, Claude Code, or similar to measurably improve team productivity and delivery speed. - Large-scale platform modernization experience including legacy transformation and cloud adoption. - Strong executive communication and senior stakeholder leadership skills.

- Expected 30% of travel, primarily to the distribution centers for go-lives, hypercare, and stakeholder engagement - May have to travel to our DC's in Memphis & other key sites regularly

Relocation assistance / allowance is not budgeted for this position