Description: Mandatory: * Bachelor’s degree in Production Engineering, Food Engineering, Industrial Administration, Statistics, Data Science, or related fields. * Prior experience in coordination, team leadership, or industrial KPI management. * Experience in industrial environments (food, beverages, CPG — critical differentiator). * Proficiency in KPI Management, data governance, and executive dashboards. * Solid knowledge of SAP, MES, and data entry systems. * Understanding of Lean methodologies and fundamentals of Operational Excellence. * Proven experience with BI platforms (Power BI, Tableau, Looker) at the governance and architecture level—not merely report consumption. * Strong SQL knowledge: ability to validate queries and understand data limitations. * Familiarity with data warehouse concepts, ETL processes, and data integrity. * Willingness to relocate and reside in Goiânia/GO. 1. Industrial Data and KPI Governance * Ensure standardization, integrity, and reliability of all factory-level KPIs (OEE, losses, efficiency, costs, productivity, quality, etc.). * Coordinate the team responsible for populating, updating, and validating industrial databases. * Guarantee that dashboards, reports, and KPIs are aligned, up-to-date, and comparable across sites. * Define rules, policies, and calculation criteria for corporate industrial KPIs. 2. Routine and Performance Ritual Management * Sustain governance of Daily Management System (DMS) across all sites. * Monitor and ensure adherence to operational rituals: * N1, N2, and N3 meetings * Deviation analysis * Action plan tracking * Visual management * Weekly and monthly factory performance rituals * Ensure consistency, discipline, and standardization in how factories analyze, escalate, and resolve issues. 2.1 Advanced Process Analytics (Process Mining) * Implement and maintain process mining programs to identify bottlenecks, deviations, and automation opportunities in critical workflows. * Use process mining tools (e.g., Celonis, SAP Signavio, UiPath) for predictive analysis of industrial losses and operational flows. * Define a digital transformation roadmap for factory processes based on data-driven insights and process mining recommendations. * Align process mining findings with Lean projects and prioritized efficiency initiatives. 3. Coordination of the Industrial Intelligence Team * Lead, guide, and develop the team responsible for: * BI dashboards * Operational analytics * Executive reporting * Root cause analysis * Review of goals and KPIs * Productivity studies * Prioritize requests, organize deliverables, and ensure alignment with factory and corporate needs. * Define work plans, methodologies, and timelines for the team. * Establish a BI governance chain: query validation, calculation documentation, and accuracy testing prior to production deployment. * Ensure continuous team training in BI tools, SQL, data governance, and analytical methodologies. 4. Operational Excellence (Strategic Level) * Ensure governance of Lean methodologies and continuous improvement practices at the macro level (governance, prioritization, standardization). * Ensure analyses, rituals, and KPIs are leveraged to drive Lean projects and efficiency initiatives. * Prioritize where and how the team should act to capture value through data. 5. Strategic Business Support * Review industrial targets and support senior leadership in defining annual objectives. * Structure executive rituals for monitoring industrial performance. * Serve as the bridge among data, factories, engineering, quality, and senior leadership—ensuring alignment and clarity. * Guarantee comparability across sites, internal benchmarking, and corporate-level analysis. * Lead organizational change related to calculation policies or new KPIs; communicate impacts to factories. * Mediate prioritization between corporate and site teams; ensure decisions are data-driven and strategically aligned. * Develop factory-based leadership to sustain rituals and analytics—reducing dependence on corporate support. 2512060202191907785