Senior Process Integration Engineer: Data-Driven Yield

Jobtailor; Arizona; On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor in Arizona is seeking a senior Process Integration leader to drive data-driven resolution of integration challenges. You will partner with engineering, integration, and manufacturing to design scalable analytics infrastructure and enable inline monitoring.

The role requires expertise in device physics, variability analysis, and predictive analytics, with leadership across cross-functional teams to optimize FEOL/BEOL processes for multiple products.

Qualifications

• Master's degree in STEM field required.
• 5+ years in Process Integration in semiconductor industry.
• Experience in high-volume manufacturing environments.
• Strong leadership and communication skills.
• PhD preferred; cross-functional leadership experience a plus.

Responsibilities

• Lead data-driven identification of process integration challenges.
• Partner with teams to design and deploy scalable data analytics infrastructure.
• Enable inline monitoring, process control, and rapid excursion detection.
• Develop variability tracking and chamber/tool matching methodologies.
• Detect variations, reduce tool-to-tool differences, improve manufacturing stability.
• Build and maintain automated databases, reporting systems, and analysis workflows.
• Support high-volume manufacturing decisions, predictive analytics, and ML-based optimization.
• Advance FEOL/BEOL process optimization across multiple products.

Skills

Process integration

Big data

Project management

Leadership

Communication

Machine learning

Fabrication process engineering

Device physics

Interconnects control

Education

Master's degree in Electrical Engineering

Ph.D. preferred

Tools

Automated databases

Reporting systems

Analysis workflows

Job description

Jobtailor in Arizona is seeking a senior Process Integration leader to drive data-driven resolution of integration challenges. You will partner with engineering, integration, and manufacturing to design scalable analytics infrastructure and enable inline monitoring.

The role requires expertise in device physics, variability analysis, and predictive analytics, with leadership across cross-functional teams to optimize FEOL/BEOL processes for multiple products.