Principal / Senior Engineer, Data Analytics & Management

RECRUITMATIC PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RECRUITMATIC PTE. LTD. searches for a senior analytics engineer to lead test analytics for wafer sort, burn-in and final test in our semiconductor client’s Singapore operations.

You will own the manufacturing analytics platform ecosystem, drive data infrastructure, and develop automation solutions with Python, SQL and BI tools to improve yield and quality across global teams.

Qualifications

• 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 ownership mindset, capable of delivering results in a dynamic startup environment.
• Strong collaboration, communication, and interpersonal skills across global teams.
• Excellent analytical and problem-solving skills with data-driven decision making.

Responsibilities

• Own test analytics strategy covering Wafer Sort, Burn-In and Final Test.
• Develop analytics solutions for yield learning, outlier detection, excursion monitoring, and quality screening.
• Define platform roadmap, governance, deployment strategy, and user adoption for analytics tools.
• Drive data infrastructure and automation across wafer, assembly, test and quality operations.
• Develop automation solutions using Python, SQL, Power BI, VBA and modern analytics tech.

Skills

Analytical mindset

Cross-functional collaboration

Communication skills

Ownership mindset

Problem solving

Teamwork

Education

Bachelor’s/Master’s/PhD in EE, Electronics, CS, Data Science, Statistics

Tools

Databricks

JMP

Power BI

Tableau

Excel/VBA

STDF

ATDF

MES

SQL

Python

Job description

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.