{"id":1021071,"url":"https://alion.io/job/qualcomm-data-engineer-staff-semiconductor-engineering","title":"Data Engineer, Staff (Semiconductor Engineering)","company":{"id":94,"name":"Qualcomm","domain":"qualcomm.com","url":"https://alion.io/company/qualcomm","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"C","score":69,"open_postings":1068,"ghost_share":0.255,"stale_share":0.147,"repost_share":0.45,"time_to_fill_p50_days":74,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":66000,"max_usd":158000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":781},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Pandas","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"C++","optional":true},{"name":"Java","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Rest-Assured","optional":true}],"status":"live","first_seen_at":"2026-07-29T00:00:00Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-11-06T07:53:20Z","board_verified":true,"closed_at":null,"days_open":100,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":100},"description":"Company:\nQualcomm Global Trading Pte. Ltd.Job Area:\nEngineering Group, Engineering Group > Software EngineeringGeneral Summary:\nRole Summary\nServe as a Staff Data Engineer leading the design and implementation of scalable data platforms, governed data products, and advanced analytics capabilities that drive semiconductor engineering insights.\n\nPartner with cross-functional teams across Test Engineering, Product Engineering, Yield, and NPI to transform complex semiconductor test data into reusable, high-quality data products and analytics solutions. Leverage cloud-native technologies to develop business logic, data pipelines, and rapid prototypes, while working closely with IT to transition solutions into production environments with strong standards for scalability, governance, reliability, and operational support.\n\nThis role plays a key part in enabling timely, trusted, and actionable insights from high-volume semiconductor data sources, improving engineering productivity, decision-making, and overall solution effectiveness.\n\nKey Responsibilities\nDesign, develop, and optimize end-to-end data products and ETL/ELT solutions for large-scale semiconductor engineering datasets, including wafer sort, final test, parametric, quality, and manufacturing data. Translate business requirements into scalable cloud-based architectures that support high-volume, high-velocity data ingestion, transformation, semantic modeling, and analytics consumption.\n\nDrive engineering analytics capabilities by implementing business logic for yield analysis, binning (hard/soft bin), parametric trend monitoring, failure analysis, and test program optimization. Partner closely with domain experts, data owners, and IT teams to rapidly prototype solutions and productionize them into reliable, observable, and governed enterprise platforms.\n\nEstablish and maintain domain data products, governance frameworks, and stewardship practices, including business glossaries, semantic definitions, data dictionaries, metadata management, lineage tracking, data quality controls, access management, and compliance requirements. Ensure trusted, discoverable, reusable, and self-service data assets that support Data Mesh principles and data-driven decision-making.\n\nContinuously improve platform scalability, performance, and reliability by applying cloud data engineering best practices, optimizing large-scale STDF/ATE data processing, implementing reusable ingestion and standardization frameworks, and enabling end-to-end traceability across test stages from wafer to package and final test.\n\nRequired Qualifications\n8-15 years of experience in Data Engineering, Data Platform Engineering, or related disciplines.\nStrong hands-on experience with cloud data platforms, preferably AWS.\nProficient in Python (PySpark, Pandas, ETL frameworks) and SQL (data modeling, optimization, and performance tuning).\nExperience designing and delivering end-to-end data solutions across the complete data lifecycle, from ingestion and transformation to serving and analytics consumption.\nHands-on experience with modern data platforms such as Databricks, Snowflake, Spark, or equivalent cloud-native technologies.\nStrong understanding of semiconductor test data domains, including yield, quality, manufacturing, and engineering analytics.\nKnowledge of Data Governance, Data Stewardship, Metadata Management, Data Quality Management, and Data Product principles.\nExperience creating and maintaining data product documentation, business glossaries, data dictionaries, lineage artifacts, and governance standards.\nUnderstanding of data ownership models, governance processes, security controls, and enterprise access management practices.\nProven ability to collaborate across business, engineering, and IT organizations to deliver scalable, governed, and production-ready data solutions.\nPreferred Qualifications\nExposure to:\nMCP / API-based data access patterns\nExperience in semiconductor / manufacturing data environments (e.g., STDF, parametric test data, yield analysis)\nAWS Certified Solution Architect - Professional\nMinimum Qualifications\nBachelor'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.\nOR\nMaster's degree in Engineering, Information Systems, Computer Science, or related field and 3+ year of Data Engineering, ETL Development experience, or related work experience.\nMinimum Qualifications:\n• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.OR\nMaster's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.\nOR\nPhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.\n• 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.\nApplicants: 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  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).\nQualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.\nTo all Staffing and Recruiting Agencies:Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. 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