Senior Director Digital Twin Manufacturing

Overview We are seeking a Sr. Director,Digital Twin Manufacturingto define, build, and scale PepsiCo’s globalManufacturing Digital Twin product lineacross the enterprise manufacturing footprint. This role is accountable for delivering a standardized portfolio of manufacturing digital twin products—Spatial,Engineering,Operational,Integrated, andAdaptive—that improve plant performance throughreal-time visibility,simulation-driven optimization, andAI/ML-enabled insights. This leader will bring a strongproduct mindsetand deep operational credibility to translate plant problems into scalable, reusable digital twin products that can be rapidly deployed across regions and sites. The role partners closely with theDigital Twin Platform & Solutionsleader (platform backbone), plant and manufacturing transformation leaders (adoption and value), and IT/OT, Data & AI, Enterprise Architecture, Cybersecurity, and strategic partners to deliver measurable improvements inOEE, throughput, quality, reliability, and downtime. Responsibilities Manufacturing Digital Twin Product Strategy (Vision, Roadmap, Scale): Own the global strategy, multi-year roadmap, and product operating model for Manufacturing Digital Twins across PepsiCo plants. Define standardized manufacturing problem statements and scalable product modules to focus investment on repeatable capabilities (vs one-off site builds). Establish product outcomes, adoption targets, and KPIs aligned to manufacturing value (e.g., OEE, downtime, yield/quality, throughput, schedule adherence). Drive global deployment strategy through site waves, readiness criteria, and scalable playbooks with manufacturing transformation and sector leaders. Engineering Twins & Simulation Products (Material Flow, Plant Trial, DES): Deliver Engineering Twins for plant layout, line design, and internal material flow—enabling what-if analysis, constraint testing, and capital planning decisions. Scale material flow simulation and discrete event simulation capabilities as reusable products/modules (not custom models per site). Enable hybrid modeling approaches including physics-based (first principles) + data-driven models where they improve fidelity and decision quality. Partner with platform and engineering teams to repatriate/standardize engineering twin development into scalable components and reference implementations. Operational Twins for Performance, Quality, and Reliability: Deliver Operational Twins that integrate IoT/telemetry, engineering data, and operational systems to drive continuous monitoring and performance optimization. Own product modules for performance twins, process/quality twins, and reliability twins including failure prediction and downtime impact simulation. Define integration patterns with plant systems (e.g., MES, SCADA/OT data sources, IoT/Edge platforms, ERP) in partnership with Enterprise Architecture and the platform team. Ensure plant-ready deployment patterns supporting edge constraints, cybersecurity controls, and sustainable run operations. Adoption, Change Leadership, and Value Realization (Global Rollout): Partner with plant leadership and manufacturing transformation teams to embed digital twins into daily management systems and decision workflows. Lead pilots-to-scale execution by codifying learnings into repeatable playbooks, training, and onboarding guides. Establish value tracking mechanisms and executive reporting for benefits realized by site and by product module. Build a global community of practice across manufacturing sites to accelerate adoption, reuse, and continuous improvement. Cross-Functional and Partner Leadership (Matrix Execution at Scale): Lead mission-based delivery execution with cross-functional stakeholders across IT/OT, Data & AI, Cybersecurity, Infrastructure, and Sector IT. Partner with strategic vendors and system integrators to deliver against roadmap with measurable milestones, quality standards, and cost discipline. Build and develop a high-performing team of product leaders and domain specialists across manufacturing digital twins. Compensation & Benefits: The expected compensation range for this position is between $157,200 - $312,000. Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process. Bonus based on performance and eligibility target payout is 30% of annual salary paid out annually mand an additional target payout of 15% of annual salary is paid out over 3 years following the end of the performance period. Long term incentive equity may be awarded based on eligibility and performance. Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement. In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility:Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan. Car allowance. Qualifications Education: Bachelor’s degree required; Master’s preferred (Industrial/Manufacturing Engineering, Computer Science, Supply Chain, Operations Research, Data/Analytics, or related). Experience 12+ years in manufacturing operations, manufacturing transformation, industrial digital product delivery, and/or enterprise technology programs. Proven experience scaling digital capabilities across multi-site manufacturing networks in a matrixed organization. Demonstrated success delivering measurable improvements in OEE, throughput, reliability, downtime, or quality via digital/analytics/simulation initiatives. Technical/Domain Expertise Strong understanding of manufacturing operations and constraints (lines, changeovers, internal logistics, quality, maintenance/reliability). Experience with simulation (material flow and discrete event simulation) and scenario planning for manufacturing environments. Familiarity with OT/edge realities and plant systems (MES/SCADA/IoT) and data integration patterns; AI/ML experience preferred. Leadership Executive influence and ability to align business and technology stakeholders globally. Strong product leadership (roadmaps, scalable features, adoption KPIs, value tracking). Ability to lead multidisciplinary teams and vendors with high accountability. Success Metrics Manufacturing Digital Twin product line deployed at scale across prioritized plants with reusable modules and repeatable deployment playbooks. Measurable improvements in OEE, downtime reduction, throughput, yield/quality, and reliability driven by digital twin adoption. Reduced time-to-deploy per plant through reuse, standardization, and platform alignment. High adoption and sustained operational usage (not “POC only”), with clear KPI-based value realization reporting. EEO Statement EEO Statement Our Company will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the Fair Credit Reporting Act, and all other applicable laws, including but not limited to, San Francisco Police Code Sections 4901-4919, commonly referred to as the San Francisco Fair Chance Ordinance; and Chapter XVII, Article 9 of the Los Angeles Municipal Code, commonly referred to as the Fair Chance Initiative for Hiring Ordinance. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. PepsiCo is an Equal Opportunity Employer: Female / Minority / Disability / Protected Veteran / Sexual Orientation / Gender Identity / Age If you'd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law and EEO is the Law Supplement documents. View PepsiCo EEO Policy. Please view our Pay Transparency Statement. #J-18808-Ljbffr PepsiCo Deutschland GmbH