Lead Process Integration Engineer - Advanced Packaging

Intel; Albuquerque (NM); On-site; USD 141,000 - 199,000; Full time

Benefits offered by this job

Stock bonuses

Health benefits

Retirement plan

Paid vacation

Job summary

Intel NM Si Manufacturing Integration is seeking an engineering leader to grow into a PI Team Lead role. You will guide teams supporting advanced packaging manufacturing, drive transfers, ramps, and sustainment while aligning with customer commitments.

Ideal candidates bring leadership, DOE, data analytics, and cross-functional collaboration skills to improve yield, quality, and manufacturing efficiency in a high-volume setting.

Qualifications

• Bachelor's or Master's in a technical engineering or science field.
• Experience in semiconductor manufacturing or advanced packaging (5+ years).
• Experience in process integration or defect reduction (5+ years).
• DOE experience (3+ years).
• Data analysis and SPC experience using JMP, SQL, PCS, or similar.

Responsibilities

• Lead technology development, transfer, and manufacturing ramp activities.
• Collaborate with Advanced Packaging HVM engineering and factory operations to support transfer, ramp, and sustainment of advanced packaging technologies.
• Identify yield limiters through data analysis and drive process improvements across multiple organizations.
• Develop inline monitoring systems, dashboards, and manufacturing health metrics to enable data-driven decisions.

Skills

Technical leadership

Cross-functional collaboration

Project management

Communication

Stakeholder management

Data-driven decisions

Manufacturing optimization

Education

Bachelor's or Master's in a technical engineering/science field

Tools

JMP

SQL

PCS

Job description

Intel NM Si Manufacturing Integration is seeking an engineering leader to grow into a PI Team Lead role. You will guide teams supporting advanced packaging manufacturing, drive transfers, ramps, and sustainment while aligning with customer commitments.

Ideal candidates bring leadership, DOE, data analytics, and cross-functional collaboration skills to improve yield, quality, and manufacturing efficiency in a high-volume setting.