Quality Assurance Engineer

Purpose

Lead the Quality Assurance effort within his/her organization, to minimize quality risks across its processes (end to end) – through their early identification and minimization/elimination.

Risk Assessment, Data Analysis, and Compliance:

• Lead quality risk assessment across the whole processes under their responsibility, and ensures they are documented and updated regularly – especially those related to new/change in process and new product introduction.
• Working with other stakeholders, identify and implement actions to minimize risks identified through risk assessments – such as codifying and leading the implementation of fir-for-purpose First Article (FA) protocol for specific component types.
• Schedule and the lead implementation of quality audits within their scope of operation.
• Lead assurance effort to ensure ongoing compliance with applicable internal, customer and industry quality and regulatory requirements.
• Lead the analysis of available data to identify key trends/causes of NCRs and Service Qualities, and the root cause(s) of those key causes.
• Perform analysis of runlife performance of installed ESP systems to identify key trends and causes, at various organizational level.
• Lead the analysis of the yield, process variance and measurements done across overall manufacturing process, to identify key processes that require improvements.
• Provide input and recommendation on how to add/update/upgrade business systems to enable incorporating various data analysis as part of routine operation.
• As Subject Matter Expert (SME), train the organization on applicable topics related to root cause analysis, statistical quality tool, reliability engineering and data analysis.
• Performs other duties as assigned.

Knowledge and Experience:

• Minimum 3 years working experience in similar role, with 2 years of practical experience in data analytics and/or reliability engineering and/or statistical quality tools.
• Practical experience in using Minitab and/or Reliasoft suite-of-software (or equivalent).
• Basic knowledge in cloud computing.
• Basic knowledge in development and use of Machine Learning and Artificial Intelligence.
• Knowledge of ISO 9001 is mandatory.
• Preferred experience in Aerospace, Automotive or Electronics industry.
• Excellent English written and verbal communication skills.

Education and Certifications:

• Bachelor (or higher) degree in any Science/Engineering discipline; Master (or higher) degree preferred.
• ASQ Certified Quality Engineer certification highly preferable.
• Six Sigma Green/Black Belt certification preferable.
• Certified auditor certification preferable.
• PMP (Project Management Professional) certification preferable.
• Familiarity with API Q1 Quality Management Standards.