Manufacturing Process Engineer II - Lean & Automation

Greene, Tweed & Co Limited

United States

On-site

USD 80,000 - 110,000

Full time

6 days ago
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Benefits offered by this job

Health insurance
401k
Life and disability insurance
Tuition assistance

Job summary

Greene Tweed is seeking an experienced Manufacturing Engineer to join our world-class operations team in the United States. You will lead continuous improvement initiatives, apply Lean Six Sigma, and drive capital projects from concept through IQ/OQPQ to production.

The ideal candidate has 3–6 years of engineering experience, strong data analysis skills, and proficiency with SPC, PFMEA, DMAIC and process-design methods to reduce scrap, improve safety, and boost process capability in a

Qualifications

  • BS Degree in Engineering is required.
  • 3–6 years engineering experience.
  • Lean/Six Sigma certification preferred.
  • Strong knowledge of SPC, PFMEA, DMAIC, and process mapping.
  • Experience with materials and polymer processing is a plus.

Responsibilities

  • Respond to metrics and collaborate with Value Stream Manager to improve machinery operations and production methods.
  • Identify root causes and implement corrective actions for safety and quality issues.
  • Lead capital expense projects from quote to IQOQPQ and participate in budgeting.
  • Promote automation in the value stream and advance total preventative maintenance.
  • Ensure compliance with safety and quality regulations and pursue Lean Six Sigma development.

Skills

Problem solving
Data analysis
Cross-functional collaboration
Decision making

Education

BS Degree in Engineering

Tools

SPC
PFMEA
DMAIC
Process Mapping
DFM
Lean Six Sigma

Job description

Greene Tweed is seeking an experienced Manufacturing Engineer to join our world-class operations team in the United States. You will lead continuous improvement initiatives, apply Lean Six Sigma, and drive capital projects from concept through IQ/OQPQ to production.

The ideal candidate has 3–6 years of engineering experience, strong data analysis skills, and proficiency with SPC, PFMEA, DMAIC and process-design methods to reduce scrap, improve safety, and boost process capability in a

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