Quality Assurance Engineer

Overview

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.

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