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Statistical Process Control Engineer Jobs in Phoenix, AZ

Senior Process Engineer #1657

Phoenix, AZ

$128K - $165K/yr

Job Title Senior Process Engineer #1657 Statement about position/company : A job at TSMC Arizona ... Apply statistical process control methods to establish and sustain a robust manufacturing process.

As a Photomask Process/Equipment Engineer, you will demonstrate a strong sense of reliability and ... Apply statistical process control methods to establish and sustain a robust photomask process flow.

As a Process Engineer , you will focus on delivering a robust and efficient semiconductor ... Applying statistical process control methods to establish and sustain a robust manufacturing ...

As a Process Engineer , you will focus on delivering a robust and efficient semiconductor ... Applying statistical process control methods to establish and sustain a robust manufacturing ...

... process. The Role This position serves as a Quality Control Engineer specialist responsible for ... The ideal candidate will be able to use their laboratory and statistical knowledge to communicate ...

... process. The Role This position serves as a Quality Control Engineer specialist responsible for ... The ideal candidate will be able to use their laboratory and statistical knowledge to communicate ...

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Statistical Process Control Engineer information

See Phoenix, AZ salary details

$52.1K

$98.1K

$146K

How much do statistical process control engineer jobs pay per year?

As of Jun 25, 2026, the average yearly pay for statistical process control engineer in Phoenix, AZ is $98,058.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $115,700.00 per year, depending on experience, location, and employer.

What does a Statistical Process Control Engineer do?

A Statistical Process Control (SPC) Engineer is responsible for designing, implementing, and maintaining systems that monitor and control manufacturing processes using statistical methods. They analyze data to identify trends, reduce process variation, and improve product quality. SPC Engineers work closely with production teams to ensure processes remain stable, efficient, and in compliance with industry standards. Their role often involves training staff in SPC techniques and troubleshooting quality issues using data-driven approaches.

What are the key skills and qualifications needed to thrive as a Statistical Process Control Engineer, and why are they important?

To thrive as a Statistical Process Control Engineer, you need a solid background in statistics, process engineering, and quality management, often supported by a degree in engineering or a related field. Familiarity with SPC software (such as Minitab or JMP), Six Sigma methodologies, and quality system certifications like ASQ are typically required. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and collaborating with cross-functional teams. These skills and qualifications are vital to maintain product quality, optimize processes, and drive continuous improvement within manufacturing or production environments.

What is the difference between Statistical Process Control Engineer vs Quality Engineer?

AspectStatistical Process Control EngineerQuality Engineer
Primary FocusMonitoring and controlling manufacturing processes using statistical methodsEnsuring overall product quality through testing, inspection, and process improvements
CertificationsSix Sigma, Statistical Process Control (SPC) certificationsSix Sigma, Quality Management certifications (e.g., CQE)
Work EnvironmentManufacturing plants, process development labsQuality departments, production facilities
Industry UsageManufacturing, automotive, electronicsManufacturing, healthcare, aerospace

While both roles focus on improving product quality, the Statistical Process Control Engineer specializes in using statistical tools to monitor and control manufacturing processes, whereas the Quality Engineer oversees broader quality assurance activities, including testing and compliance. Understanding these differences helps in choosing the right career path or job search focus.

How does a Statistical Process Control Engineer typically collaborate with production and quality teams to drive process improvements?

A Statistical Process Control Engineer regularly works alongside both production and quality assurance teams to identify trends, troubleshoot issues, and implement data-driven improvements. They analyze real-time data from manufacturing processes, facilitate root cause analysis sessions, and communicate findings through reports or presentations. Collaboration often includes training team members on SPC tools and methodologies, as well as guiding them in using statistical techniques to monitor and control process variability. This cross-functional teamwork ensures that process adjustments are both technically sound and operationally practical, leading to sustained quality improvements.
What are popular job titles related to Statistical Process Control Engineer jobs in Phoenix, AZ? For Statistical Process Control Engineer jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Statistical Process Control Engineer jobs in Phoenix, AZ look for? The top searched job categories for Statistical Process Control Engineer jobs in Phoenix, AZ are:

Engineer II, Process

LG Energy Solution Arizona

Queen Creek, AZ • On-site

Other

Posted 13 days ago


Job description

Job Summary: 

The Process Engineer II is responsible for independently driving process performance, yield improvement, quality enhancement, and operational excellence within the Electrode Manufacturing area. This role serves as a technical subject matter expert for assigned manufacturing processes and equipment, leading complex troubleshooting efforts, process optimization projects, new technology implementation, and production ramp-up activities. The Process Engineer II partners closely with Production, Quality, Equipment Engineering, Maintenance, and R&D teams to improve safety, quality, delivery, and cost performance.

Responsibilities:

  • Lead investigations of complex process and quality issues, identify root causes, and implement effective corrective and preventive actions (CAPA) to prevent recurrence.
  • Independently analyze manufacturing data and process performance metrics to identify trends, variation sources, and improvement opportunities.
  • Design, execute, and lead Design of Experiments (DOE) activities to optimize process capability, product quality, throughput, and cost.
  • Own and continuously improve key manufacturing performance indicators including OEE, yield, scrap, process downtime, cycle time, and productivity.
  • Lead qualification activities for new materials, equipment, tooling, and process technologies, including validation of process changes and performance verification.
  • Develop technical reports and present findings, recommendations, and project updates to plant leadership and cross-functional stakeholders.
  • Drive continuous improvement initiatives utilizing Lean Manufacturing, Six Sigma, Statistical Process Control (SPC), and other problem-solving methodologies.
  • Lead non-conformance investigations and implement robust containment, corrective action, and long-term preventive measures.
  • Develop, maintain, and improve PFMEAs, Process Flow Diagrams (PFDs), Control Plans, process specifications, and manufacturing standards.
  • Evaluate and approve 4M (Man, Machine, Material, Method) changes and support New Product Introduction (NPI), process transfers, and manufacturing ramp-up activities.
  • Serve as technical lead for assigned production lines by providing advanced troubleshooting support for process and equipment-related issues.
  • Collaborate with Equipment Engineering and Maintenance teams to improve equipment reliability, process stability, and manufacturing capability.
  • Analyze process capability and establish statistical control strategies to reduce variation and improve product consistency.
  • Develop and revise SOPs, work instructions, and engineering standards to support operational excellence.
  • Train and mentor Process Engineer I team members, technicians, and production personnel on process technologies, troubleshooting methodologies, and best practices.
  • Support implementation of automation, digital manufacturing, and smart factory initiatives to improve operational efficiency.
  • Participate in customer audits, internal audits, and quality system activities as required.
  • Perform other duties as assigned.

Qualifications:

  • Bachelor's degree in Chemical Engineering, Materials Engineering, Mechanical Engineering, Industrial Engineering, Electrical Engineering, or related engineering discipline required.
  • Minimum 3 years of manufacturing engineering experience, preferably in lithium-ion battery manufacturing, semiconductor, automotive, chemical processing, or other high-volume manufacturing environments.
  • Experience supporting electrode manufacturing processes including mixing, coating, drying, calendering, slitting, or related technologies preferred.
  • Demonstrated experience leading process improvement projects and cross-functional technical initiatives.

Skills:

  • Strong knowledge of DOE, Statistical Process Control (SPC), Process Capability Analysis, Six Sigma, and root cause analysis methodologies.
  • Experience utilizing quality tools including PFMEA, Control Plans, 8D, Fishbone Analysis, Pareto Analysis, and Failure Analysis techniques.
  • Ability to analyze large manufacturing datasets and translate findings into actionable process improvements.
  • Proficiency with statistical analysis software such as Minitab, JMP, or equivalent analytical tools.
  • Strong understanding of manufacturing process control and process validation methodologies.
  • Ability to independently manage multiple projects and priorities in a fast-paced manufacturing environment.
  • Strong technical writing, presentation, and communication skills.
  • Effective collaboration and leadership skills with cross-functional teams.
  • Ability to mentor junior engineers and provide technical guidance to manufacturing personnel.
  • Strong problem-solving skills with a data-driven and continuous improvement mindset.