Senior Product Development Test Engineer, Data Analytics
Qualcomm · Singapore, Central Singapore, Singapore ·
- Work mode
- Onsite
- Seniority
- Senior
- Category
- Data analytics
- Experience
- 1+ years
Qualcomm · Singapore, Central Singapore, Singapore ·
General Summary:
Role Summary
We are seeking a Senior Data Engineer to design and deliver end-to-end data solutions that support domain-driven analytics and fast-evolving business requirements within semiconductor test engineering environments.
This role focuses on business logic development, cloud-based ETL design, and rapid prototyping, working closely with domain teams (e.g., Test Engineering, Product Engineering, Yield, and NPI teams) to translate complex test data requirements into scalable solutions. You will also partner with IT to transition prototypes into production-grade pipelines, ensuring maintainability, scalability, and governance.
The role is critical in strengthening our ability to deliver complete, high-quality data solutions, especially for high-volume semiconductor test data (e.g., STDF, parametric, wafer sort, final test, and reliability data), while improving turnaround time and solution effectiveness.
Key Responsibilities
Design and implement end-to-end ETL/ELT pipelines (ingestion → transformation → modeling → consumption) for large-scale semiconductor test data (wafer sort, final test, and parametric datasets)
Develop business logic and data transformations aligned with test engineering workflows, including binning (hard/soft bin), yield analysis, and parametric trend evaluation
Rapidly prototype data solutions to support evolving analytics, yield improvement initiatives, and test program optimization use cases
Translate business needs into scalable and maintainable data architectures that support high-volume, high-velocity test data ingestion and processing
Partner with IT to productionize pipelines, ensuring reliability, monitoring, observability, and governance for mission-critical test data systems
Improve existing pipelines by applying cloud ETL best practices, with a focus on performance optimization for large STDF/ATE data and distributed processing
Ensure data quality via validation, reconciliation, and consistency checks, including test data integrity, bin definition alignment, and cross-stage traceability (wafer → package → final test)
Support domain teams with data modeling, usability, and performance improvements tailored for engineering analytics, yield dashboards, and failure analysis workflows
Enable data lineage and traceability across test stages, supporting root cause analysis and engineering debug
Drive reusable patterns and frameworks for faster solution delivery, particularly for test data ingestion, normalization, and standardization across suppliers (eg. OSATs, foundries)
Required Qualifications
5–10 years in Data Engineering / Platform Engineering
Strong experience in cloud data platforms (AWS required)
Hands-on expertise in:
Python (PySpark, Pandas, ETL frameworks)
SQL (data modeling, performance tuning)
Experience with:
Experience designing end-to-end data solutions, not just individual components
Strong understanding of data lifecycle (ingestion → transformation → serving)
Experience working with platforms such as Databricks / Snowflake / Spark-based systems
Preferred Qualifications
Experience with Data Mesh / Domain Data Product architecture
Familiarity with:
Metadata platforms (Data Catalog, Glue Catalog, Unity Catalog)
RAG / AI data pipelines / vector stores
Exposure to:
Agentic AI architecture (skills, tools, API-based consumption)
MCP / API-based data access patterns
Experience in semiconductor / manufacturing data environments (e.g., STDF, parametric test data, yield analysis)
AWS Certified Solution Architect - Professional
Minimum Qualifications
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 5-10 years of Data Engineering, ETL Development experience, or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ year of Data Engineering, ETL Development experience, or related work experience.
Minimum Qualifications:
• Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail [email protected] or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
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