Principal / Senior Engineer, Data Analytics & Management

My client is a large fabless Semiconductor Company in Singapore.

Key Responsibilities

• Test Analytics & Quality Screening
• Own the test analytics strategy covering Wafer Sort (WS), Burn-In (BI) and Final Test (FT).
• Develop advanced analytics solutions for yield learning, outlier detection, excursion monitoring, statistical screening, and quality monitoring.
• Support implementation and optimization of quality screening methodologies including PAT, Statistical Bin Limits (SBL), dynamic guard-banding, clustering, and test escape prevention.
• Collaborate with Product Engineering and Test Engineering teams to improve outgoing quality performance and reduce DPPM.
• Analytics Platform Ownership
• Own the manufacturing analytics platform ecosystem, e.g. JMP, Power BI, Databricks, and yield related tools.
• Define platform roadmap, governance, deployment strategy, and user adoption plans.
• Establish best practices for analytics development, data governance, reporting standards, and engineering productivity.
• Provide technical leadership for tool evaluations, vendor engagement, implementation, and user training.
• Fabless Operations Systems & Tool Setup
• Define system requirements and integration strategies between Foundries, OSATs, MES, Quality Management Systems, and analytics platforms.
• Drive standardization of manufacturing data flows, system interfaces, and engineering workflows.
• Develop operational tools to support NPI, qualification, production ramp, and mass production activities, e.g. process release, deviation material management, change management.
• Data Infrastructure & Automation
• Own end-to-end semiconductor manufacturing data ecosystem across wafer, assembly, test and quality operations.
• Design and manage manufacturing data solutions, including databases, ETL pipelines, dashboards, cloud architectures, and automated reporting systems.”
• Develop automation solutions using Python, SQL, Power BI, VBA, and modern analytics technologies to improve engineering productivity.

Qualifications

Required:

• Bachelor's, Master's, or PhD in Electrical Engineering, Electronics Engineering, Computer Science, Data Science, Statistics, or related fields.
• Minimum 5+ years (Senior Engineer) or 8+ years (Principal Engineer) of semiconductor industry experience in data analytics, analytics platforms and data architecture.
• Experience analyzing semiconductor manufacturing, yield, test, reliability, and quality datasets.
• Hands-on experience with STDF, ATDF, MES, manufacturing databases, and semiconductor data ecosystems.
• Self-motivated, hands-on team player with a strong ownership mindset, capable of delivering results in a dynamic and rapidly growing startup environment.
• Strong collaboration, communication, and interpersonal skills, with the ability to work effectively across global and multicultural teams.
• Excellent analytical and problem-solving skills, combining data-driven decision-making with sound engineering judgment.

Technical Expertise:

• Experience with Databricks, JMP, Yield tools or equivalent semiconductor analytics platforms.
• Experience with Statistical Process Control (SPC), PAT, SBL, outlier detection, clustering analysis, and quality screening techniques.
• Proficiency in SQL, Python, JMP, Power BI, Tableau, Excel/VBA, or equivalent analytics tools.
• Experience leading digital manufacturing, analytics platform, AI-based analytics or data transformation initiatives.
• Knowledge of ATE test operations and test methodologies.
• Understanding of semiconductor manufacturing flows including Wafer Sort, Assembly, Final Test, Reliability, and Quality operations.

Kris Lam (R1983356)

Director

Recruitmatic Pte. Ltd. (22S1186)

2 Venture Drive #14-02

Vision Exchange S

608526