Senior Manager, Operational Excellence

Summary: At The   Coca ‑ Cola   Company, operational excellence is core to delivering trusted and exceptional beverage experiences at scale. Within Global Equipment Platforms (GEP), the   Senior Manager, Operational Excellence   plays a critical role in advancing reliability, performance, and cost efficiency for our global fleet of dispensing, cooling, and vending platforms. This role leads the charge in transforming equipment lifecycle management—from   design   through end-of-life—by applying predictive analytics, automation, and continuous improvement methodologies to achieve world-class quality outcomes.   As   Coca ‑ Cola   accelerates innovation, this position   leverages   reliability engineering principles alongside digital technologies such as AI-driven modeling and IoT-enabled monitoring. Through collaboration with bottlers, operating units, and cross-functional teams, you will champion strategies that embed lifecycle performance into design,   validate   endurance using accelerated life testing, and close the feedback loop between field data and future platforms. An ideal candidate combines engineering rigor, operational mindset, and digital fluency to streamline validation cycles, sustain first-time quality, and modernize equipment testing in line with our global transformation roadmap.     What   You’ll   Do for Us   Own lifecycle quality and reliability performance for beverage equipment platforms, ensuring durability and uptime targets are met pre- and post-launch.   Conduct accelerated life and service validation testing,   leveraging   endurance simulations and highly automated lab infrastructure to prove system integrity across service cycles.   Apply Reliability-Centered Maintenance (RCM), Failure Modes and Effects Analysis (FMEA), and root cause methodologies to   eliminate   recurring field failures and design in reliability.   Define preventive and predictive maintenance standards for global execution through locally managed operating units and bottler networks.   Drive continuous improvement initiatives by integrating Lean, Six Sigma, and Total Productive Maintenance (TPM) methods to enhance efficiency and sustain equipment performance across geographies.   Lead modernization of testing capabilities through lab digitalization and automation strategies that enable touchless, data-driven validation workflows.   Apply AI-enabled reliability modeling tools (digital twins, Weibull, Bayesian analysis) to predict failure points, shorten validation timelines by at least 50%, and improve scale-up confidence.   Leverage   IoT-connected monitoring solutions to stream real-time performance data from the field, accelerating response   times   and closing the design feedback loop.   Define, track, and cascade reliability metrics—including MTBF, MTTR, OEE, first-time quality, and total cost of ownership—across equipment platforms and regional networks.   Collaborate across global and local teams to integrate field learnings into next-generation platform designs and influence decision-making through actionable insights.     Requirements & Qualifications   Bachelor’s degree in Mechanical , Reliability, Industrial   Engineering   or related technical discipline; advanced degree or professional reliability certification (CRE) preferred.   Significant experience   in reliability engineering, equipment development, and accelerated life testing within global manufacturing or equipment environments.   Deep knowledge of reliability methodologies including RCM, FMEA, and root cause analysis, combined with proven application of Lean, Six Sigma (Black Belt preferred), and TPM principles.   Strong capabilities in digital transformation for testing ecosystems and automation of validation processes using advanced lab technologies.   Fluency in reliability data modeling techniques (digital twin, Weibull analysis, Bayesian prediction) and deployment of