Senior Manager, Operational Excellence

The Coca-Cola Company•Atlanta, GA

1d•$131,000 - $153,000•Onsite

About The Position

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.

Requirements

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 AI-enabled predictive solutions.
Experience leveraging IoT connectivity and advanced analytics to monitor equipment health and optimize lifecycle performance.
Familiarity with operational KPIs such as MTBF, MTTR, availability, OEE, first-time quality, and total cost of ownership, and ability to operationalize these across networks.
Demonstrated capacity to influence functional and regional stakeholders in a matrixed global organization to implement operational excellence initiatives.
Strong analytical, technical, and communication skills to translate data-driven insights into actionable business strategies.

Nice To Haves

advanced degree or professional reliability certification (CRE)
Six Sigma (Black Belt preferred)

Responsibilities

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.