Manufacturing Engineering Supervisor: Process Improvement

PHINIA; Rzeszów; On-site; PLN 187,000 - 281,000; Full time

Job summary

PHINIA, a premium solutions provider, seeks a Manufacturing Engineering Supervisor for its Rzeszów area. You will supervise a team of engineers, drive process optimization, and implement advanced manufacturing technologies while ensuring compliance with APQP and IATF 16949 standards.

You will collaborate across quality, logistics and production to document processes, analyze data, and support customers with new products through robust problem-solving and statistical methods.

Qualifications

• Higher technical education in mechanical or production/industrial engineering.
• 5 years of experience in process engineering, production, quality or project management.
• Experience managing employees, preferably in automotive.

Responsibilities

• Supervise the process engineering team and drive continuous improvement.
• Oversee process optimization and adoption of advanced manufacturing tech.
• Plan and document processes per APQP and IATF 16949.
• Coordinate cross-functional teams and benchmark PHINIA facilities.
• Provide analyses and support for process improvement initiatives.
• Support customers in new product implementation using APQP.
• Improve process capability for special characteristics with statistics.
• Organize, schedule, and supervise subordinate staff.

Skills

Mechanical engineering

Production engineering

Industrial engineering

Team management

Lean manufacturing

Six Sigma

IATF 16949 knowledge

FMEA

Statistical analysis

Education

Bachelor's degree in Mechanical/Production/Industrial Engineering

Tools

APQP

Problem-solving tools

Job description

PHINIA, a premium solutions provider, seeks a Manufacturing Engineering Supervisor for its Rzeszów area. You will supervise a team of engineers, drive process optimization, and implement advanced manufacturing technologies while ensuring compliance with APQP and IATF 16949 standards.

You will collaborate across quality, logistics and production to document processes, analyze data, and support customers with new products through robust problem-solving and statistical methods.