{"schemaVersion":"jobsearcher.job.v1","id":"66dc8da5f8d0b66354d6fbb0","url":"https://jobsearcher.com/jobs/66dc8da5f8d0b66354d6fbb0","canonicalUrl":"https://jobsearcher.com/jobs/66dc8da5f8d0b66354d6fbb0","title":"Process Integration Engineer","description":"The Process Integration (PI) Engineer is responsible for Solar cell Efficiency and Yield in fast-paced manufacturing environment. PI Engineer focus on the maintenance, and optimization of solar cell testing tools, including current–voltage (IV) measurement, Electroluminescence (EL) and Automated Optical Inspection (AOI) systems. The role also involves conducting failure analysis using offline metrology tools, advanced data analysis, and implementing yield improvement strategies to support manufacturing excellence.\n\nResponsibilities\n\nInline Inspection System Ownership (IV / EL / AOI)\n\nOversee the operation, calibration, and maintenance of solar cell testers, including inline testing systems such as IV, EL and AOI.\n\nTroubleshoot and resolve issues related to tester performance to ensure accurate data collection and minimal downtime using data-driven and physics-based approaches.\n\nEnsure accuracy, calibration, and stability of IV, EL, and AOI systems, including validation of key electrical parameters (Voc, Isc, FF) and benchmarking against offline metrology tools.\n\nDrive improvements in defect detection algorithms and classification methods using EL, AOI, and offline metrology data.\n\nConduct detailed failure analysis of solar cells using offline metrology tools, such as photoluminescence (PL), quantum efficiency (QE), infrared imaging, and advanced microscopy, to identify root causes of defects and quantify loss mechanisms impacting efficiency and yield.\n\nSupport root cause analysis of process-related defects by combining inline tester results with offline failure analysis findings and correlating to upstream and downstream process steps.\n\nIdentify dominant yield loss pareto and prioritize improvement actions based on impact to efficiency and throughput.\n\nTranslate defect analysis findings into actionable process improvements by solving issues through data analysis, experimentation (e.g., DOE), and collaboration with subject matter experts across relevant process steps.\n\nData Analysis & Monitoring\n\nDevelop and implement yield monitoring strategies, integrating data from inline testers, metrology tools, and MES systems to track performance and identify gaps and enable continuous improvement.\n\nPerform advanced data analysis using tools like JMP and Tableau to detect patterns and trends, providing actionable recommendations to improve production yield and product quality.\n\nDevelop automated data pipelines and scripts (coding experience in Python, JSL or similar languages is a plus) to streamline data processing and analysis.\n\nEnsure data traceability across inline systems, offline metrology, and MES to support accurate defect tracking and root cause analysis.\n\nSafety & General Responsibilities\n\nExecute all required duties while practicing safe work methods and adhering to all plant safety rules.\n\nPerform other duties and special projects, as assigned by management.\n\nQualifications\n\nBachelor’s degree in technical discipline, Engineering experience in a manufacturing setting.\n\nExperience in solar cell manufacturing is preferred.\n\nStrong mechanical aptitude and analytical approach.\n\nProven technical acumen.\n\nEngineering degree or equivalent technical college diploma.\n\nThe ability to effectively interface with all management levels and other client business units.\n\nCoding experience in Python, R, or other scripting languages is a plus for automating data processing and analysis workflows.\n\nProficiency in data analysis tools like JMP, Tableau, or equivalent platforms, with the ability to extract insights from complex datasets.\n\n#J-18808-Ljbffr","company":"Es Foundry","rawCompany":"es foundry","city":"Columbia","state":"SC","isRemote":false,"isActive":true,"createdAt":"2026-06-20T03:50:30.452Z","occupations":[{"code":"17-2199.11","title":"Solar Energy Systems Engineers","slug":"solar-energy-systems-engineers"},{"code":"17-2112.00","title":"Industrial Engineers","slug":"industrial-engineers"},{"code":"17-2112.03","title":"Manufacturing Engineers","slug":"manufacturing-engineers"}],"industries":[{"code":"221114","title":"Solar Electric Power Generation","slug":"solar-electric-power-generation"},{"code":"334413","title":"Semiconductor and Related Device Manufacturing","slug":"semiconductor-and-related-device-manufacturing"},{"code":"334419","title":"Other Electronic Component Manufacturing","slug":"other-electronic-component-manufacturing"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Process Integration Engineer","description":"The Process Integration (PI) Engineer is responsible for Solar cell Efficiency and Yield in fast-paced manufacturing environment. PI Engineer focus on the maintenance, and optimization of solar cell testing tools, including current–voltage (IV) measurement, Electroluminescence (EL) and Automated Optical Inspection (AOI) systems. The role also involves conducting failure analysis using offline metrology tools, advanced data analysis, and implementing yield improvement strategies to support manufacturing excellence.\n\nResponsibilities\n\nInline Inspection System Ownership (IV / EL / AOI)\n\nOversee the operation, calibration, and maintenance of solar cell testers, including inline testing systems such as IV, EL and AOI.\n\nTroubleshoot and resolve issues related to tester performance to ensure accurate data collection and minimal downtime using data-driven and physics-based approaches.\n\nEnsure accuracy, calibration, and stability of IV, EL, and AOI systems, including validation of key electrical parameters (Voc, Isc, FF) and benchmarking against offline metrology tools.\n\nDrive improvements in defect detection algorithms and classification methods using EL, AOI, and offline metrology data.\n\nConduct detailed failure analysis of solar cells using offline metrology tools, such as photoluminescence (PL), quantum efficiency (QE), infrared imaging, and advanced microscopy, to identify root causes of defects and quantify loss mechanisms impacting efficiency and yield.\n\nSupport root cause analysis of process-related defects by combining inline tester results with offline failure analysis findings and correlating to upstream and downstream process steps.\n\nIdentify dominant yield loss pareto and prioritize improvement actions based on impact to efficiency and throughput.\n\nTranslate defect analysis findings into actionable process improvements by solving issues through data analysis, experimentation (e.g., DOE), and collaboration with subject matter experts across relevant process steps.\n\nData Analysis & Monitoring\n\nDevelop and implement yield monitoring strategies, integrating data from inline testers, metrology tools, and MES systems to track performance and identify gaps and enable continuous improvement.\n\nPerform advanced data analysis using tools like JMP and Tableau to detect patterns and trends, providing actionable recommendations to improve production yield and product quality.\n\nDevelop automated data pipelines and scripts (coding experience in Python, JSL or similar languages is a plus) to streamline data processing and analysis.\n\nEnsure data traceability across inline systems, offline metrology, and MES to support accurate defect tracking and root cause analysis.\n\nSafety & General Responsibilities\n\nExecute all required duties while practicing safe work methods and adhering to all plant safety rules.\n\nPerform other duties and special projects, as assigned by management.\n\nQualifications\n\nBachelor’s degree in technical discipline, Engineering experience in a manufacturing setting.\n\nExperience in solar cell manufacturing is preferred.\n\nStrong mechanical aptitude and analytical approach.\n\nProven technical acumen.\n\nEngineering degree or equivalent technical college diploma.\n\nThe ability to effectively interface with all management levels and other client business units.\n\nCoding experience in Python, R, or other scripting languages is a plus for automating data processing and analysis workflows.\n\nProficiency in data analysis tools like JMP, Tableau, or equivalent platforms, with the ability to extract insights from complex datasets.\n\n#J-18808-Ljbffr","datePosted":"2026-06-20T03:50:30.452Z","dateModified":"2026-06-20T03:50:30.452Z","hiringOrganization":{"@type":"Organization","name":"Es Foundry","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Columbia","addressRegion":"SC","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"66dc8da5f8d0b66354d6fbb0"},"url":"https://jobsearcher.com/jobs/66dc8da5f8d0b66354d6fbb0"}}