Wafer Process Engineer: Yield & Process Improvement

Catalyst Talent Strategy Consulting; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Catalyst Talent Strategy Consulting is seeking a Process Engineer for our client in Singapore's semiconductor manufacturing network. The role focuses on wafer process control, quality and yield goals, and cross-functional collaboration with global Technology teams.

The successful candidate will apply DOE, SPC and data analysis to drive continuous improvement, troubleshoot yield losses, and implement best practices across production lines.

Qualifications

• University degree in Engineering or Science.
• Knowledge of quality management systems, data analysis, DOE and SPC.
• Proficient in JMP, Visual Basic; database queries a plus.
• Self-motivated and team-oriented.
• Good analytical and communication skills.
• Willingness to learn.

Responsibilities

• Manage wafer manufacturing process to meet quality, yield, and production targets.
• Collaborate with Technology counterparts globally on process alignment and qualification of new processes, suppliers and consumables if needed
• Work with cross-functional teams on process capability improvement and yield enhancement projects
• Coordinate troubleshooting of process issues and yield losses
• Drive for continuous process improvement and permanent solutions to resolve chronic process and quality issues.
• Develop best practices and routine solutions for continuous improvement
• Perform statistical data analysis for process improvement and interpretation of data
• Apply problem solving methods (8D, Fishbone, DOE) and risk analysis (like FMEA)

Skills

Quality management

Data analysis

DOE

SPC

Problem-solving

Education

Bachelor's degree in Engineering or Science

Tools

JMP

Visual Basic

Database queries

Job description

Catalyst Talent Strategy Consulting is seeking a Process Engineer for our client in Singapore's semiconductor manufacturing network. The role focuses on wafer process control, quality and yield goals, and cross-functional collaboration with global Technology teams.

The successful candidate will apply DOE, SPC and data analysis to drive continuous improvement, troubleshoot yield losses, and implement best practices across production lines.