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Statistical Process Control Engineer Jobs in Arizona

Statistical Process Control and Design of experiments (DOE) principles, Statistical Data Analysis (Examples include: JMP/JSL, Python, SQL) Preferred Qualifications: * Programing Experience in JMP/JSL ...

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 ...

Statistical Process Control and Design of experiments (DOE) principles, Statistical Data Analysis (Examples include: JMP/JSL, Python, SQL) Preferred Qualifications: * Programing Experience in JMP/JSL ...

Process Control Technician 3rd Shift 10:00pm- 6:30am Monday- Friday Job Summary: We are seeking a ... Proficient in quality processes and statistical techniques. * Knowledgeable with tape measures and ...

Process Control Technician 3rd Shift 10:00pm- 6:30am Monday- Friday Job Summary: We are seeking a ... Proficient in quality processes and statistical techniques. * Knowledgeable with tape measures and ...

... 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 ...

Analyze statistical process control performance, OOC's and trend alerts. Requires use of Excel, JMP or other statistical software. * Lead Process Engineering Development * Direct and oversee process ...

Analyze statistical process control performance, OOC's and trend alerts. Requires use of Excel, JMP or other statistical software. * Lead Process Engineering Development * Direct and oversee process ...

Conduct and document trend review investigationAnalyze statistical process control performance, OOC ... Lead Process Engineering DevelopmentDirect and oversee process improvement initiatives for Fujifilm ...

Analyze statistical process control performance, OOC's and trend alerts. Requires use of Excel, JMP or other statistical software. * Lead Process Engineering Development * Direct and oversee process ...

As a Packaging Module Development Engineer, you will: • Contribute to the advancement of ... Statistical Process Control (SPC) and/or Design of Experiments (DOE) • Delivery of results for ...

Showing results 21-40

Statistical Process Control Engineer information

What is statistical process control in engineering?

Statistical Process Control (SPC) is a method used by engineers, including those in quality and manufacturing roles, to monitor and control a process through statistical analysis of data. It involves using control charts and data collection to detect variations, ensuring processes operate consistently and within specified limits. SPC helps improve product quality and reduce defects by identifying and addressing process issues early.

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.

How much do statistical process control engineers make in the US?

Statistical Process Control (SPC) engineers in the US typically earn between $70,000 and $110,000 annually, with the median salary around $85,000. Salaries vary based on experience, industry, location, and certifications such as Six Sigma or quality management training.

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

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 Arizona? For Statistical Process Control Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Statistical Process Control Engineer jobs in Arizona look for? The top searched job categories for Statistical Process Control Engineer jobs in Arizona are:
What cities in Arizona are hiring for Statistical Process Control Engineer jobs? Cities in Arizona with the most Statistical Process Control Engineer job openings:
Infographic showing various Statistical Process Control Engineer job openings in Arizona as of June 2026, with employment types broken down into 66% Full Time, 32% Part Time, and 2% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Process Integration Engineer

INTEL

Phoenix, AZ

$116K - $163K/yr

Full-time

Medical, Retirement, PTO

Posted 14 days ago


Intel rating

8.7

Company rating: 8.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

19th of 156 rated electronics manufacturers


Job description

Job Description

Job Description

Intel is looking for highly motivated individuals with strong technical background and capabilities to sustain, ramp, and transfer all technology nodes in Arizona. They will drive rapid continuous improvements in safety, quality, yield, reliability, cost, process stability/capability, and productivity while maintaining rigorous quality control.

The role of a Process Integration and Yield Engineer is to deliver high quality analytical insights that influences / directs the factory resources to minimize defects, control process parameters, and improve overall factory yields. All improvements and sustaining work is done in close collaboration and partnership with the process to improve the capability of the tools and processes.

Responsibilities may include, but are not limited to:

  • Performing detailed data analysis using various statistical/data mining tools to identify the root cause of defect and yield issues.
  • Identifying exclusionary or baseline sources of defects or yield impacts and recommending/leading corrective actions/fixes.
  • Lead/participate continuous improvement projects on products and processes for improved performance.
  • Provide expertise on process flow segments.
  • Lead/participate in multi-area problem solving teams to provide expertise to troubleshoot complex yield problems.

The ideal candidate should exhibit the following behavioral traits:

  • Solid analytical skills and a passion for data analysis and problem solving.
  • Organizational skills with attention to detail.
  • Excellent interpersonal skills with the ability to work with people at all levels.
  • Communication and presentation skills to influence a wide variety of groups at all levels.
  • Demonstrate excellent teamwork and leadership skills, demonstrated problem solving and prioritization skills, and driving high performance maintenance goals for the group.

Qualifications

Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications:

  • BSE degree in Electrical Engineering, Microelectronics Engineering, Material Science Engineering, Chemical Engineering, Mechanical Engineering, Optical Engineering, Statistics/Data Science, Chemistry, Physics or related field of study with 4+ years of experience, or Master’s degree with 3+ years of experience or a Ph.D. in the above labeled fields.
  • Depending on the degree level obtained, the mentioned years of experience will be needed in each of the below areas:
    • Knowledge of Semiconductor fabrication and processing techniques (Lithography, Etch, CMP, Thin Films, Plating, etc.)
    • Statistical Process Control and Design of experiments (DOE) principles, Statistical Data Analysis (Examples include: JMP/JSL, Python, SQL)

Preferred Qualifications:

  • Programing Experience in JMP/JSL, Python, R and SQL
  • 2+ yrs of New Technology startup experience
  • 5+ years of advanced node Foundry experience in Process/Yield Engineering.

Posting Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Benefits
We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here.
Annual Salary Range for jobs which could be performed in the US $116,100.00-$163,800.00
*Salary range dependent on a number of factors including location and experience
Working Model
This role will require an on-site presence.* Job posting details (such as work model, location or time type) are subject to change.

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About Intel

Sourced by ZipRecruiter

Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore's Law to bring smart, connected devices to every person on Earth

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1968