ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Support Manufacturing Engineering team in resolving production capacity‑related issues
- Assist in productivity and DGR improvement activities through data analysis and process studies
- Support capacity line setup, line conversion, scheduling, and production ramp‑up activities
- Participate in day‑to‑day production capacity and output gap analysis and issue resolution
- Support OEE / TEEP data collection, analysis, and improvement initiatives
- Assist in coordinating manufacturing cost improvement projects
- Support capital budget requests, purchase requisitions, and on‑time equipment ordering tracking
- Develop and improve team processes by creating or supporting digital applications using AI, Industry 4.0 (4IR), and other digital technologies to improve efficiency
This position is part of our Early Career program at WD. Our Early Career program is designed to support individuals beginning their professional career by providing the foundational training through a structured onboarding, mentorship, and development curriculum.
REQUIRED:
We warmly welcome fresh graduates of a Master's degree, and Early Career Talent with 0–2 years of experience are encouraged to apply.
- Currently pursuing or recently completed Master's degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering, or equivalent experience
- Fundamental understanding of manufacturing processes, production flow, and capacity concepts gained through coursework or academic projects
- Basic knowledge of productivity improvement and industrial engineering principles (e.g., line balancing, cycle time, throughput)
- Introductory understanding of OEE / equipment efficiency metrics
- Ability to support production capacity and output gap analysis under guidance
- Basic awareness of manufacturing cost concepts and willingness to participate in cost improvement activities
- Willingness to learn and assist with capital equipment justification, purchase requests, and order tracking
- Strong interest in applying AI, Industry 4.0, and digital technologies to improve manufacturing efficiency
PREFERRED:
- Internship, co‑op, or project experience in a manufacturing or production environment
- Exposure to line setup, line conversion, or production ramp‑up through internships or university projects
- Coursework or project experience in Lean Manufacturing, Six Sigma, or Continuous Improvement
- Experience using data analysis tools (Excel, dashboards, basic simulations) for capacity or productivity analysis
- Academic or project exposure to AI, data analytics, automation, smart manufacturing, or digital factory concepts
- Familiarity with manufacturing KPIs such as output, yield, OEE, or cycle time
SKILLS:
- Fundamental manufacturing engineering and process analysis skills
- Basic capacity planning and productivity improvement skills
- Data analysis and structured problem‑solving ability
- Ability to support OEE/TEEP improvement activities
- Strong learning agility and willingness to work hands‑on in a production environment
- Teamwork and collaboration with Manufacturing Engineering and Operations teams
- Clear communication and basic technical presentation skills
- Proficiency in Microsoft Excel and PowerPoint
- Curiosity and an innovative mindset toward AI, 4IR, and digital application development
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WD thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.
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Notice To Candidates: Please be aware that WD and its subsidiaries will never request payment as a condition for applying for a position or receiving an offer of employment. Should you encounter any such requests, please report it immediately to WD Ethics Helpline or email compliance@wdc.com.