Quality Control Engineering Intern

JOB DESCRIPTION

As a Quality Control Intern for Arconic in Cranberry Township, you will be a part of a large Quality Control Team helping support one of Arconic's largest aluminum extrusion facilities. Working closely with the Quality Engineer, Quality Manager and the Quality Team, the Quality Intern will help support the various efforts that drive our high standards of quality for our products made at the Cranberry Facility.

This internship offers immersive, hands‑on experience in statistical methods, process optimization, and problem solving. A significant portion of your work will involve learning manufacturing processes, working with operators and engineers, and translating findings into actionable improvements.

Basic Qualifications

• Must be enrolled in an accredited institution pursuing a bachelor's degree in engineering, operations, or a related technical field.

• Employees must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is not available for this position.

Preferred Qualifications

• Experience with precision measurement tools (micrometers, calipers, height gauges).

• Familiarity with SPC, basic statistical methods, or data‑driven quality techniques.

• Proficiency in Microsoft Office and analytical tools such as Minitab or Power BI.

• Workflow development, creating SWI, SOP and other technical documentation.

• Ability to interpret mechanical and test data, including PSI, force, and dimensional measurements.

• Assist in gathering, organizing, and preparing production and quality data for engineering analysis.

• Use and apply statistical process control and analytical techniques to assess process reliability and identify potential quality leaks.

• Use engineering problem‑solving tools such as cause‑and‑effect diagrams, 5‑Why analysis, fishbone diagrams, and correlation‑based exploratory methods.

• Apply predictive or inferential techniques to support data‑driven decision making.

• Participate in Gemba floor engagements to validate technical conclusions with real process behavior and safety practices.

• Support the creation or improvement of data visualization and reporting tools that enhance continuous improvement and engineering decisions.

• Assist in gathering, organizing, and preparing production and quality data for engineering analysis.

• Use and apply statistical process control and analytical techniques to assess process reliability and identify potential quality leaks.

• Use engineering problem‑solving tools such as cause‑and‑effect diagrams, 5‑Why analysis, fishbone diagrams, and correlation‑based exploratory methods.

• Apply predictive or inferential techniques to support data‑driven decision making.

• Participate in Gemba floor engagements to validate technical conclusions with real process behavior and safety practices.

• Support the creation or improvement of data visualization and reporting tools that enhance continuous improvement and engineering decisions.