Shift Fab Operations Engineer (Wet Process)

Micron Technology, Inc.; Boise (ID); On-site; USD 70,000 - 90,000; Full time

Job summary

Micron Technology, Inc. in Boise, Idaho seeks a New College Graduate Shift Manufacturing Engineer to drive daily fab performance in Wet Process Operations.

The role works with technicians, engineers and operations to meet wafer move targets and improve cycle time on a 12-hour shift. The position emphasizes data analysis, problem solving, and cross-functional collaboration, with opportunities to leverage AI tools to enhance decision-making and productivity in a fast-paced manufacturing

Qualifications

• Bachelor's degree or equivalent experience in Industrial Engineering, Manufacturing Engineering, Operations Management, Supply Chain, Engineering, or a related technical field.
• Proven analytical and problem-solving skills.
• Ability to work in a fast-paced manufacturing environment.

Responsibilities

• Supervise wafer movement performance by DID, process step, and operational targets.
• Identify manufacturing gaps, WIP imbalances, bottlenecks, and workflow disruptions.
• Develop and implement plans to close gaps and achieve weekly move and wafer-on-hand commitments.
• Support operational decision-making to optimize capacity utilization and factory performance.
• Partner with Engineering teams to prioritize and communicate tool-related needs.
• Support automation, reporting, and process improvements that improve visibility and decision-making.

Skills

Industrial Eng.

Manufacturing Eng.

Data analysis

Python/SQL

Education

Bachelor's degree in Industrial Engineering

Tools

Python

SQL

Tableau

Power BI

Job description

Micron Technology, Inc. in Boise, Idaho seeks a New College Graduate Shift Manufacturing Engineer to drive daily fab performance in Wet Process Operations.

The role works with technicians, engineers and operations to meet wafer move targets and improve cycle time on a 12-hour shift. The position emphasizes data analysis, problem solving, and cross-functional collaboration, with opportunities to leverage AI tools to enhance decision-making and productivity in a fast-paced manufacturing