Data Analytics Quality Engineering Manager

Renesas Electronics; Ipoh; On-site; MYR 180,000 - 300,000; Full time

Job summary

Renesas Electronics in Malaysia is seeking a Data Analytics Quality Engineering Manager to lead a data analytics team and strengthen subcontractor quality assurance across manufacturing and supply chain.

You will drive data pipelines, ELT processes, automated testing, and governance while delivering real-time dashboards using Spotfire and Power BI. Collaboration with internal and external teams is essential for timely improvements.

Qualifications

• Degree in electrical engineering or related field with focus on semiconductor.
• Minimum 7 years of relevant experience in data analysis with a track record of driving improvements.
• Strong statistical analysis knowledge and data governance experience.

Responsibilities

• Lead a small data analytics engineering team in ecosystem development and integration with upstream and downstream processes.
• Define and work with subcontractors on internal databases, support data pipeline development, and ELT processes.
• Implement automated testing, write data validation scripts, and establish data governance to ensure data integrity.
• Model and transform data for dashboards (Spotfire) to track supplier outputs and defect rates in real time.
• Provide quick data analysis to identify drifts and enable counter-action plans.
• Analyze manufacturing data trends to identify deviations for long-term improvements.

Skills

Data analytics

Agile

Leadership

Problem solving

Communication

Education

Degree in electrical engineering or related field

Tools

Spotfire

PowerBI

JMP

Minitab

Job description

Data Analytics Quality Engineering Manager

• Full-time
• Employment Type: Regular (PERM)
• Remote Work Available: No

Renesas is seeking a Data Analytics Quality Engineering Manager for its outsourced foundry, assembly, and test subcontractor management. The role hybridizes subcontractor quality assurance with advanced data analytics for data visualization, statistical modeling, and data‑driven decision making to track, predict, and resolve manufacturing variabilities and supply chain continuity.

Key Responsibilities

• Lead a small data analytics engineering team in ecosystem development and integration with upstream and downstream processes.
• Define and work with subcontractors on establishing internal databases, support data pipeline development, and maintain ELT (Extract, Load, Transform) processes.
• Implement automated testing, write data validation scripts, and establish data governance to ensure data integrity and accuracy.
• Perform data modeling and transformation for interactive dashboards (e.g., Spotfire) to track supplier key output responses and defect rates in real time.
• Support quick data analysis to identify drifts in manufacturing lines and provide immediate feedback for counter‑action plan execution.
• Analyze manufacturing data trends to identify deviations for mid‑ to long‑term improvement initiatives.

Qualifications

• Degree in electrical engineering or related field with focus on semiconductor.
• Minimum 7 years of relevant experience in data analysis with a track record of driving improvements or product engineering.
• Strong statistical analysis knowledge.
• Experience with semiconductor products and processes (fab, assembly, test, post‑test).
• Agile and highly motivated, capable of designing data analytics ecosystems.
• Proficient in problem‑solving methodologies such as 8D, 5‑Why, and Fishbone analysis.
• Experience using analysis software (e.g., JMP, Minitab, Spotfire, PowerBI).
• Excellent communication and interpersonal skills when working with internal and external functional groups.
• Experience or knowledge in predictive analytics.
• Proven ability to influence teams and drive timely resolution of potential quality issues.
• Experience working with AI, ML, Digital Twins, Cloud and Edge Computing.

Equal Opportunity Statement

Renesas Electronics is an equal‑opportunity and affirmative‑action employer, committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by law. For more information, please read our Diversity & Inclusion Statement.