ProductionReports to: Operations ManagerLocation: Leioa, Basque Country, SpainTerms & Conditions: Full-time Local TermsA strong candidate has been identified through our succession planning.While a strong internal candidate has been identified through our succession planning process, we remain open to additional applications to ensure that all individuals who meet the required skills, performance, experience, and leadership criteria outlined in the JD have a fair opportunity to be considered.All resumes must be in English.The role is critical to the development of the factory (zero defects, zero waste, zero losses), applying the full range of Focused Improvement methods across Safety, Quality, Business Priority/Cost Deployment, Autonomous Maintenance, Customer Service and Agility. Contributes directly to the development of semi-autonomous teams, ensuring high standards of safety, quality, efficiency and sustainability.Most Complex Aspects of the RoleRoot-cause analysis of losses across complex, multi-variable production problems, applying the full UMS toolset (FI, AM, PM, Q,



PD).Proposing and validating effective countermeasures and technical standards while balancing safety, quality, cost and delivery.Driving consistent digital/automation deployment across lines with varying technical maturity.KEY RESPONSIBILITIESAnalyse losses and operational problems, identifying root causes through direct floor observation, data analysis and hands-on involvementDesign and drive action plans and Run to Standard (R2S) implementation (data collection/analysis, loss prioritisation, problem solving, SMED, AM activities and machine settings/centerlines), building multidisciplinary teamsEstablish and validate technical standards defining basic operating conditionsAct as technical trainer for line teams, coaching in phenomena identification, root-cause analysis and establishment of countermeasuresAnalyse operational data — including accuracy of MMP Code data — to detect patterns and mak

📌 Process Engineer (Madrid)
🏢 Unilever
📍 Madrid