WD is building the infrastructure behind the AI-driven data economy.

As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time. That's where we come in.

We combine deep engineering expertise with global-scale manufacturing to deliver the storage systems that make AI possible, powering hyperscale data centers, cloud platforms, and enterprise infrastructure worldwide.

This isn't theoretical work. It's real systems, at real scale, people solving some of the hardest challenges in technology today.

We're looking for people who want to build, solve, and operate at that level.

Join us and let's shape the future of data.

Job Description

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.

Qualifications

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 degreein 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

Additional Information

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.

WD is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at [HIDDEN TEXT] to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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 [HIDDEN TEXT].

Senior Engineer, Manufacturing Engineering