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ZT Systems · 12 hours ago

Principal Quality Engineer

Secaucus, NJ

Full-time

Onsite

Lead/Staff

$141K/yr - $188K/yr

10+ years exp

ZT Systems, a Sanmina Company, is seeking a Principal Quality Engineer to lead the development of data-driven quality systems in manufacturing. This role involves collaborating across various teams to enhance production quality and reliability through advanced analytics and smart factory methods.

Cloud ComputingCloud InfrastructureInternet

H1B Sponsor Likely

Responsibilities

Lead or contribute to transformation initiatives, helping set new standards for how ZT approaches manufacturing risk analysis, quality, and continuous improvement

Define and implement new systems, processes, or frameworks that support the smart factory vision, including automation, metrology, advanced inspection and testing, and predictive analytics

Collaborate across design, quality, manufacturing, test, and supplier engineering to drive solutions that integrate seamlessly into production

Develop, implement, and sustain Statistical Process Control (SPC) systems using industry-standard software

Lead Gauge R&R studies and measurement system analysis to ensure measurement accuracy and reliability

Translate DFM and PFMEA insights into actionable process risk controls across production lines

Perform advanced data analysis to identify trends, detect anomalies, and support predictive quality

Lead supplier qualification, audits, and ongoing supplier quality management, ensuring robust quality throughout the supply chain

Implement and maintain data traceability systems for compliance, customer requirements, and continuous improvement

Support new customer engagement, including quality requirement review, contract manufacturing quality alignment, and onboarding of customer-specific standards

Drive structured problem-solving initiatives for both internal and supplier-related issues

Partner with design, operations, and manufacturing teams to ensure quality during new product introduction (NPI)

Explore and deploy AI and automation technologies (machine vision, predictive analytics, anomaly detection, digital twins) to enhance manufacturing quality and efficiency

Ensure compliance with industry quality standards (ISO 9001, IATF 16949, or similar)

Qualification

Statistical Process Control (SPC)Predictive analyticsData analysisAutomation technologiesMinitabPythonSQLGauge R&RPFMEACoachingContinuous improvementCommunicationMentoringProblem-solvingCollaborationLeadership

Required

Advanced degree in Engineering, Computer Science, Data Science, or a related field

10–15 years of experience in high-volume, high-complexity manufacturing, with at least 5 years in leadership or transformation roles (not necessarily people management)

Demonstrated expertise in statistical and analytical methods such as regression analysis, correlation analysis, DOE, SPC, PFMEA, Gauge R&R, and commonality studies

Proficiency with data-driven tools such as Minitab, JMP, Python, R, SQL (or equivalent) to analyze and interpret large, complex datasets

Track record of driving measurable improvements in yield, reliability, or process robustness

Excellent communication skills with the ability to engage at both executive and technical levels

Background in electronics assembly, PCBA, servers, or other high-reliability industries (e.g., aerospace, medical devices, automotive, etc.)

Experience coaching or mentoring technical teams to upskill in data-driven decision-making

Proficiency in CAD tools (SolidWorks, AutoCAD) and industrial automation platforms (Siemens, Allen-Bradley, etc.)

Experience with PLC programming, robotic integration (e.g., 6-axis arms, gantry systems), and industrial sensors

Familiarity with MES systems, Python, or SQL for automation control