Senior Engineer, Customer Quality Engineering

Company Description

At Western Digital, our vision is to power global innovation and push the boundaries of technology to make what you thought was once impossible, possible.

At our core, Western Digital is a company of problem solvers. People achieve extraordinary things given the right technology. For decades, we’ve been doing just that—our technology helped people put a man on the moon and capture the first-ever picture of a black hole.

We offer an expansive portfolio of technologies, HDDs, and platforms for business, creative professionals, and consumers alike under our Western Digital®, WD®, and WD_BLACK™.

We are a key partner to some of the largest and highest-growth organizations in the world. From enabling systems to make cities safer and more connected, to powering the data centers behind many of the world’s biggest companies and hyperscale cloud providers, to meeting the massive and ever-growing data storage needs of the AI era, Western Digital is fueling a brighter, smarter future.

Today’s exceptional challenges require your unique skills. Together, we can build the future of data storage.

Job Description

As a Senior Engineer in the Product Insights team, you will collect, analyze, and communicate product performance data from the field to help WD deliver world-class storage solutions. . You’re someone who enjoys solving puzzles and digging into the ‘why’ behind customer and field issues. You'll partner with Customer Quality Management (CQM), Engineering, and Quality teams to translate complex datasets into actionable insights that prevent issues, improve products, and enhance customer experience.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Data Analysis & Reporting

• Analyze telemetry data, PAC (Product Analysis Center) reports, FIRs (Failure/Issue Reports), and RMA trends to identify quality issues and failure patterns
• Build dashboards and visualizations to track product health metrics (e.g., failure rates, NTF rates, SMART attributes, vendor logs)
• Generate regular reports and ad-hoc analyses for leadership, Engineering, and Sales teams
•  Use curiosity‑driven investigation to chase down unusual trends, unexpected behaviors, or anomalies in telemetry and RMA data.

Cross-Functional Collaboration

• Partner with CQM to prioritize customer quality issues and drive root cause investigations
• Work with Engineering to validate product improvements and track effectiveness of corrective actions
• Support Applications Engineering and Product Marketing with field performance data for new product introductions (NPI)
•  Act as a “data detective,” helping teams understand not just what happened, but why it happened.

Predictive Analytics & Insights

• Develop models to predict failure modes and identify at-risk product populations
• Conduct cohort analysis to compare performance across firmware versions, regions, and customer segments
• Proactively flag emerging issues before they impact customers at scale

Process Improvement

• Enhance data collection, storage, and analysis workflows
• Drive standardization of metrics and reporting across product lines
• Champion data quality and governance within the PI team

What We Offer

• Opportunity to impact product quality for millions of customers worldwide.
• Collaborative culture with cross-functional exposure across WD
• Access to cutting-edge data platforms and analytics tools
• Professional development and growth within a newly formed, strategic organization

Qualifications

REQUIRED:

• Education: Bachelor's degree in Data Science, Statistics, Engineering, Computer Science, or related field
• Experience: Several years in data analysis, product analytics, or quality engineering (storage industry preferred)

SKILLS:

• Technical Skills:
  • Proficiency in SQL, Python, R, or similar analytics tools
  • Experience with BI platforms (Tableau, Power BI, Looker, etc.)
  • Strong Excel/Google Sheets skills for quick analysis
  • Familiarity with statistical methods and data modeling
  • Familiarity with programming fundamentals and the ability to leverage AI‑powered coding tools (e.g., Windsurf) to write, review, and modify code.
• Domain Knowledge:
  • Understanding of storage products (HDDs, SSDs) and SMART data (preferred)
  • Knowledge of quality processes (RMA, PAC, failure analysis) a plus
• Communication: Ability to translate technical findings into business-relevant insig