Senior Engineer, Production Test Process

About our group:

The Process Engineering team at Seagate Singapore is responsible for developing, sustaining, and improving core backend HDD manufacturing processes. We partner closely with operations, equipment engineering, automation, industrial engineering, and quality teams to ensure high yield, cost efficient, and robust manufacturing performance.
Our team drives process capability improvements, statistical analysis, DOE studies, and qualification activities to support both high volume manufacturing and new product introduction (NPI).

About the role - you will:

. Own and sustain critical backend manufacturing processes-monitor daily yield, SPC trends, scrap, and key process indicators.
. Perform structured root cause analysis (5 Why, Fishbone, DMAIC) to resolve process excursions and chronic issues.
. Lead design of experiments (DOE), process characterization, Gage R&R, and capability (Cp/Cpk) studies.
. Partner with equipment and automation teams to drive process equipment optimization, recipe refinement, and failure mode reduction.
. Develop and release process documentation, work instructions, PFMEA, and control plans aligned with Seagate's quality system.
. Support NPI builds, engineering trials, tool conversions, and qualification activities (IQ/OQ/PQ).
. Evaluate process robustness, introduce new materials/consumables, and work with suppliers on quality and performance improvements.
. Drive continuous improvement projects focused on yield uplift, cycle time reduction, cost improvements, and process digitization.

About you:

. Strong analytical, statistics, and problem solving skills.
. Detail oriented with a structured, data driven approach.
. Hands on, proactive, and comfortable working in a fast paced manufacturing environment.
. Collaborative communicator across multi functional teams.
. Open to travel to Thailand for one month for On-the-job training.

Your experience includes:

. Bachelor's degree in Mechanical, Electrical, Materials, Chemical, Mechatronics, or related engineering discipline.
. Experience in high volume manufacturing with SPC, DOE, process optimization, and root cause analysis.
. Familiarity with metrology tools, characterization techniques, and precision measurement systems.
. Knowledge of Lean/Six Sigma tools and problem solving frameworks.

You might also have:

. Experience in HDD, semiconductor, or precision engineering industries.
. Exposure to JMP/Minitab, data analytics tools, or Python for statistical analysis.
. Experience leading cross functional improvement projects.
. Understanding of automation interfaces, equipment process interactions, and Industry 4.0 initiatives.