Hybrid Lean Manufacturing Process Engineer

Placements24; Klerksdorp; Hybrid; ZAR 480,000 - 720,000; Full time

Benefits offered by this job

Annual raises

Healthcare coverage

Hybrid work arrangement

Professional certifications

Training opportunities

Job summary

Placements24 is seeking a Manufacturing Process Engineer to join our Klerksdorp-based production team. The role focuses on analyzing and optimizing manufacturing processes to boost efficiency and maintain high quality.

You will apply lean principles, Six Sigma, and data analysis to identify bottlenecks, implement improvements, and support continuous improvement in a robust manufacturing environment.

Qualifications

• Bachelor's degree in mechanical or industrial engineering.
• Minimum of 4 years in manufacturing process engineering or similar.
• Strong knowledge of lean, Six Sigma and continuous improvement tools.
• Experience with process simulation and data analysis.
• Excellent analytical, problem-solving and communication skills.

Responsibilities

• Analyze existing manufacturing processes to identify inefficiencies and waste.
• Develop, implement, and monitor new manufacturing processes and production methodologies.
• Utilize lean manufacturing principles and Six Sigma tools to drive operational excellence and cost reduction.
• Collaborate with production teams to troubleshoot process-related issues and implement corrective actions.
• Design and implement process controls and quality assurance measures to ensure product consistency.
• Document all process changes, procedures, and training materials.

Skills

Lean manufacturing

Six Sigma

Data analysis

Process simulation

Analytical skills

Communication skills

Education

Bachelor's degree in Mechanical or Industrial Engineering

Job description

Placements24 is seeking a Manufacturing Process Engineer to join our Klerksdorp-based production team. The role focuses on analyzing and optimizing manufacturing processes to boost efficiency and maintain high quality.

You will apply lean principles, Six Sigma, and data analysis to identify bottlenecks, implement improvements, and support continuous improvement in a robust manufacturing environment.