Senior Data Analytics Quality Engineer

Renesas is seeking for a Data analytics supplier quality engineer for its Outsourced foundry, assembly and test subcontractor management. The Data Analytics SQE hybridizes subcontractor quality assurance with advanced data analytics for data visualization, statistical modeling to track, predict and resolve manufacturing variabilities and supply chain continuity. This role will build the foundations for smart manufacturing. This task requires weekend support on a rotational basis.

1. Supplier Data Integrity Management

Define and work with subcontractors on establishing internal database. Support the data pipeline development and maintain ELT (Extract, Load, Transform). Implement automated testing, write data validation scripts, and establish data governance to ensure data integrity and accuracy.

2. Automated Data Dashboard and Real time analytics

Perform Data modeling and Transformation for interactive dashboards (e.g., using Spotfire) to track supplier’s key output responses, and defect rates in real-time.

Support quick data analysis for identifying drifts in manufacturing line for immediate feedback loop for immediate counter action plan execution.

3. Manufacturing metrics improvements through continuous improvement initiatives,

Analyze manufacturing data trends to identify deviations for mid to long term optimization.

Requirements

Degree in electrical/mechanical engineering or relevant field; Minimum 2 years of relevant experience in data analysis; Possess statistical analysis knowledge; Experienced in semiconductor products and processes (Fab, Assembly, Test, Post Test); Agile and highly motivated personalities.; Hands-on experience with problem-solving methodologies such as 8D, 5-Why, and Fishbone analysis; Experience in using analysis software (E.g: JMP, Minitab, Spotfire, PowerBI); Excellent communication and interpersonal skills when working with internal and external functional groups.

Nice to have

Experience or knowledge in data analytics or predictive analysis.; Proven ability to influence team and drive timely resolution of potential quality issues; Experience working with Artificial Intelligence (AI) and Machine Learning(ML), Digital Twins, Cloud & Edge Computing.