Engineer, Supplier Quality Engineering – Strategic & Innovation

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.

ESSENTIAL DUTIES AND RESPONSIBILITIES

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 Bachelor's degree, and Early Career Talent with 0–2 years of experience are encouraged to apply.

Responsibilities

We are seeking a motivated Early Career Talent (ECT) to join the Supplier Quality Engineering (SQE) team with a focus on digital transformation.; This role provides a unique opportunity to apply engineering fundamentals, quality systems, data analytics, and Digital tools to transform supplier quality management processes; The candidate will work closely with cross-functional teams and suppliers to improve quality performance, drive automation, support the Industry 4.0 journey, and enable predictive quality through data and AI; Key responsibility: Collect, analyze, transform, and visualize supplier quality data using Python, SQL, Power BI, or equivalent tools; Assist in developing and maintaining data pipelines, digital dashboards, automated reports, and data-driven decision-making tools for SQE, including digital transformation projects; Participate in supplier workshops and training to promote digital adoption and continuous improvement

Requirements

Currently pursuing or recently completed a Bachelor's degree in Data Science, Computer Science, Computer/Software Engineering, Electrical/Electronics Engineering, Mechanical Engineering, or equivalent experience; Internship experience in manufacturing, process improvement, or digital transformation; Exposure to Six Sigma tools; Experience or familiarity with data analytics tools; Good knowledge of Data Engineering, including ETL/ELT processes and data pipelines; Good knowledge and skills in Machine Learning and Deep Learning; Knowledge in Automated Workforce projects and digital transformation; Knowledge of Python libraries such as Pandas, NumPy, and Scikit-learn; Basic knowledge of web application development, REST API, and backend development; Good English communication skills, verbal and written

Nice to have

Strong knowledge and skills in Python programming and SQL; Strong knowledge of database concepts, SQL querying, data modeling, and data transformation; Strong skills in data analysis and data processing using Python and SQL; Knowledge or experience in Generative AI, LLMs, RAG, and AI Agent development is preferred.