Global Quality FrontEnd Central Quality Assurance Remote Operation Control Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Global Quality FrontEnd Central Quality Assurance Remote Operation Control Engineer based in India.

Join a global quality engineering organization responsible for centralized quality operations across semiconductor manufacturing sites in Asia and the United States. In this role, you will help safeguard product quality through automated screening, wafer lot disposition, statistical risk assessment, and data-driven operational controls. You will combine semiconductor process knowledge, advanced analytics, automation, and quality engineering to identify risks and prevent quality escapes. The position offers broad exposure to manufacturing, product engineering, reliability, and global quality operations. You will collaborate with teams across multiple sites to standardize quality practices and improve the scalability of centralized operations. This is an opportunity to contribute to advanced semiconductor manufacturing while helping shape increasingly automated and data-driven quality systems.

Accountabilities:: Design and develop quality screening strategies, business rules, and disposition plans for centralized quality systems.

Configure and maintain automated lot-hold, disposition, and containment workflows, ensuring robust controls and interlocks are in place to minimize quality escapes and operational risks.

Collaborate with cross-functional stakeholders to establish risk-based quality control methodologies and validate enhancements to quality systems.

Evaluate wafer lots affected by planned or unplanned manufacturing deviations and determine appropriate dispositions based on electrical test data, physical characterization, process history, and statistical analysis.

Interpret outlier signals, defect signatures, excursion indicators, and other quality signals to support disposition decisions related to manufacturing excursions, quality deviations, fab conversions, and special work requests.

Document disposition decisions and provide clear technical rationale to relevant stakeholders.

Analyze large manufacturing datasets to identify abnormal signatures, trends, and emerging quality risks.

Develop and apply statistical methodologies for outlier detection, screening optimization, excursion monitoring, distribution analysis, SPC review, baseline trending, and risk assessment.

Create dashboards, metrics, and reporting solutions that improve operational visibility and support data-driven decision-making.

Support AI, machine learning, predictive analytics, and other digital transformation initiatives aimed at automating quality monitoring and disposition processes.

Partner with software development teams to define requirements and deploy scalable automation, workflow, and decision-support solutions.

Work closely with site quality teams and global stakeholders to align quality execution, share best practices, and standardize processes across manufacturing locations.

Support root-cause investigations and corrective/preventive action (CAPA) activities, contributing technical analysis and recommendations.

Communicate technical findings, recommendations, risks, and business impacts clearly to technical and non-technical stakeholders.

Develop and maintain operational procedures, business process documentation, training materials, quality metrics, and performance indicators.

Lead or participate in cross-functional continuous improvement initiatives focused on productivity, quality, automation, and operational excellence.

Support audits, compliance reviews, and quality system assessments while driving greater consistency and scalability across centralized quality operations.

Requirements:

Bachelor's degree in Electrical Engineering, Electronics Engineering, Materials Science, Statistics, or a related technical discipline; a Master's degree in Electrical/Electronics Engineering, Statistics, Data Analytics, or a related field is preferred.

3–5 years of experience in semiconductor manufacturing, product engineering, quality engineering, reliability, test engineering, or a closely related industry.

Strong understanding of statistical methodologies, including Statistical Process Control (SPC), outlier detection, distribution analysis, trend analysis, data visualization, and risk assessment.

Practical knowledge of semiconductor manufacturing processes, wafer fabrication, probe testing, and parametric testing methodologies.

Understanding of quality systems, risk management, defect containment, and quality disposition processes.

Strong analytical and problem-solving abilities, with the capacity to interpret complex manufacturing datasets and translate findings into actionable recommendations.

Experience with quality engineering, reliability engineering, or semiconductor product disposition is an advantage.

Familiarity with memory technologies such as DRAM, NAND, HBM, or other emerging memory products is preferred.

Exposure to machine learning, predictive analytics, or AI-enabled manufacturing applications is beneficial.

Experience developing dashboards using Tableau, Power BI, Spotfire, or similar visualization platforms is a plus.

Familiarity with enterprise automation, workflow systems, and digital transformation initiatives is desirable.

Knowledge of quality methodologies such as FMEA, CAPA, 8D, Six Sigma, or Lean Manufacturing is an advantage.

Strong written and verbal English communication skills, with the ability to present technical findings clearly.

Demonstrated ability to collaborate effectively across global, multicultural, and cross-functional teams.

Strong organizational skills and the ability to manage multiple priorities while maintaining accuracy and attention to detail.

Self-motivated, accountable, and proactive, with a strong ownership mindset and commitment to continuous improvement.

Experience supporting operational teams across multiple manufacturing sites is preferred.

Benefits:

Opportunity to contribute to advanced semiconductor manufacturing and next-generation memory technologies.

Exposure to global quality operations across multiple manufacturing locations and international teams.

Hands-on experience with advanced statistical analysis, automated quality systems, data analytics, and digital transformation.

Opportunities to work with AI, machine learning, predictive analytics, and automation applications in manufacturing.

Cross-functional collaboration with quality, reliability, product engineering, manufacturing, and software development teams.

Professional development opportunities in semiconductor quality engineering and operational excellence.

Opportunity to contribute to global standardization, continuous improvement, and scalable quality processes.

Full-time employment based in Hyderabad, India.

Competitive compensation and benefits package, subject to applicable employment terms and policies.

Inclusive and collaborative work environment focused on innovation, integrity, operational excellence, and continuous learning.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1