Operational Excellence Engineer — Data-Driven Process Improvement

Mondelez España Galletas Production SLU; Charleville-Mézières; On-site; EUR 42,000 - 65,000; Part time

Job summary

Mondelēz International is seeking a CI/Process Excellence professional to support continuous improvement initiatives and manage data quality within our DMS framework. You will train teams, collect data, and drive root-cause analysis to close KPI gaps. A strong lean/TPM background and Excel proficiency are required.

The role emphasizes data-driven decisions, standardization of work processes, and collaboration across departments to sustain improvements.

Qualifications

• CI and high-performance work systems experience.
• Strong facilitation and communication skills.
• Application of lean and/or TPM tools in a factory or operations environment.
• Ability to manipulate and validate data in manual and automated systems.
• Mastery of Excel and other data analytics tools.
• Organized and disciplined to support and educate on the DMS process.
• Logical and structured thinking to extract insights from data.

Responsibilities

• Provide training on CI tools and techniques. You will also help departments follow our established daily management system (DMS)
• Help teams collect data or extract it from the system to support CI activities and the DMS
• Facilitate root-cause analysis to address identified losses and departmental KPI scorecard gaps
• Establish new work standards to sustain improvement
• Train and qualify colleagues on CI tools and new work standards resulting from CI activities

Skills

CI experience

Facilitation

Data analytics

DMS knowledge

Tools

Excel

Data validation tools

Job description

Mondelēz International is seeking a CI/Process Excellence professional to support continuous improvement initiatives and manage data quality within our DMS framework. You will train teams, collect data, and drive root-cause analysis to close KPI gaps. A strong lean/TPM background and Excel proficiency are required.

The role emphasizes data-driven decisions, standardization of work processes, and collaboration across departments to sustain improvements.