Plant Operations Performance Engineer — Optimize Reliability

Dow Chemical; Caryville (TN); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

On-site fitness facilities

Employee discounts

Generous vacation policy

Job summary

Dow's Emulsions/Polymers production facility in Knoxville, TN seeks an Operations Performance Engineer to improve plant value through EH&S excellence, reliability, and cost efficiency. You will partner with Operations, Maintenance, EH&S, and other functions to optimize performance and enable safe, reliable production of quality products.

Responsibilities include troubleshooting, data-driven optimization, and ensuring MET is effectively applied.

Qualifications

• Bachelor's degree in engineering required by January 2027 (Chemical or Mechanical preferred).
• Experience in a chemical production facility preferred.
• U.S. work authorization required; no visa sponsorship available.

Responsibilities

• Work closely with the operations team leveraging problem-solving skills and technical expertise.
• Elevate knowledge of the plant and technology using historical data and SMEs.
• Ensure MET is understood and that process automation is used to optimize plant performance.
• Diagnose and document root causes of asset utilization losses in the facility.
• Provide leadership and optimization in Raw Material Efficiency, including yield and waste considerations.
• Ensure compliance with plant operating permits and support site integration.

Skills

Process Optimization

Technical Expertise

Problem-Solving Skills

Collaboration & Communication

Education

Bachelor's degree in Engineering

Job description

Dow's Emulsions/Polymers production facility in Knoxville, TN seeks an Operations Performance Engineer to improve plant value through EH&S excellence, reliability, and cost efficiency. You will partner with Operations, Maintenance, EH&S, and other functions to optimize performance and enable safe, reliable production of quality products.

Responsibilities include troubleshooting, data-driven optimization, and ensuring MET is effectively applied.