Senior Customer Quality Engineer

Seagate Technology•Shakopee, MN

2d•$81,536 - $116,596•Onsite

About The Position

The Customer Quality Engineering (CQE) team partners with major OEM, Cloud, and Channel customers to deliver a strong total customer experience through qualification readiness, failure analysis leadership, and closed-loop corrective action. We work cross-functionally with Design, Reliability, Factory Engineering, Released Product Teams, worldwide FA labs, and customer technical teams to prevent escapes, resolve escalations, and improve quality operating mechanisms and artifacts so they are repeatable and audit-ready. This role owns end-to-end customer quality for major accounts across qualification, pilot, and sustaining phases. It leads complex customer escalations with a strong emphasis on Failure Analysis (FA) management, corrective action closure (8D), and customer-facing technical communications. The role serves in a customer-facing CQE capacity, supporting OEM, Cloud, and channel customers while partnering closely with design, reliability, factory engineering, released product teams, worldwide FA labs, and customer teams to drive an exceptional total customer experience. The individual will operate with significant autonomy, drive cross-functional alignment, and strengthen CQE operating rhythm and artifacts (trackers, repositories, lessons learned, readiness documentation) so work products are repeatable, auditable, and resilient to transitions.

Requirements

Proven technical owner who thrives in customer-facing situations and can lead ambiguous, high-impact quality escalations to closure.
Strong written and verbal communicator who can explain complex technical and quality topics clearly to both internal teams and external customers.
Data-first mindset: comfortable working with messy, high-volume datasets and challenging conclusions until evidence supports them.
Demonstrated ability to influence without authority, align cross-functional teams, and drive closure with disciplined program management.
Practical and responsible AI user who understands the importance of validation, data governance, and IP protection.
Experience supporting enterprise storage products (HDD), including qualification/pilot readiness, integration support, and field escalation management.
Demonstrated experience in customer quality engineering, reliability/quality engineering, failure analysis, factory/test engineering, or a closely related technical role.
Demonstrated ability to lead structured problem-solving (8D or equivalent) and drive corrective actions through verified closure.
Strong written and verbal communication skills suitable for customer-facing technical work and cross-functional leadership.
Bachelor’s degree in engineering related field (i.e. Electrical, Mechanical, Chemical, Computer Engineering, Materials, Physics, or Information Technology) and 5+ years of experience or master’s degree in the same and 3+ years’ experience or PhD and 0+ years’ experience or equivalent experience and education.

Nice To Haves

Demonstrated ownership of FA request management and synthesis of lab findings into defensible customer narratives.
Experience with SQL and data visualization tools (Tableau, Power BI) and/or handling large log or telemetry‑style datasets.
Experience leading customer-facing technical reviews, crafting executive-ready communication packages, and influencing decisions with evidence-based risk framing.
Working knowledge of reliability metrics and modeling concepts (AFR/FR, confidence bounds, sample-size limitations) and how to communicate them responsibly.
Experience improving team operating mechanisms (trackers, templates, readiness documentation, lessons learned repositories) to improve audit readiness and transition resilience.

Responsibilities

Serve as the CQE lead for assigned major customer account(s), owning quality execution across qualification, pilot, and sustaining phases.
Drive qualification readiness and execution (Pilot/RTS), including execution tracking, risk assessment, and crisp status reporting to internal stakeholders and customers.
Own customer-facing Failure Analysis (FA) requests end-to-end: prioritize, route, track turnaround time, challenge conclusions as needed, and synthesize findings into clear, data-backed narratives for internal/external audiences.
Lead and author customer corrective action responses (8D or customer-required formats), coordinating cross-functional teams through containment, root cause, corrective action verification, and sustained closure.
Develop and present customer communication packages that clearly articulate issue description, scope/impact assessment, containment, risk evaluation, and action plans; maintain action trackers and ensure closure discipline.
Proactively identify emerging risks from qualification/field signals and drive cross-functional mitigation plans before they become customer escalations.
Build and maintain analytics pipelines for quality signals (qualification logs, FA outputs, reliability metrics, integration/field data, and customer telemetry) to identify trends, outliers, and emerging risks.
Create lightweight automation and tools (Python, SQL, dashboards) to reduce manual effort in recurring CQE workflows such as log parsing, data preparation, reporting, and action tracking.
Apply statistical reasoning to support reliability and quality narratives, including trend analysis, failure-rate concepts, confidence in conclusions, and appropriate handling of small or incomplete data sets.
Use Generative AI responsibly to accelerate CQE work products (e.g., drafting technical summaries, synthesizing FA findings, proposing next-step experiments, generating first-pass 8D content), while validating outputs against source data and complying with data classification and IP protection rules.
Apply structured problem-solving methodologies (8D, closed-loop corrective action discipline, root cause analysis) and support issue tracking through verified closure.
Develop working knowledge of enterprise storage qualification expectations, endurance and reliability definitions, and how test results translate to customer risk.
Perform and validate log and telemetry analysis using approved internal tools; ensure supporting evidence is properly captured and linked in tracking systems for cross-team visibility.
Demonstrate strong data stewardship, documentation discipline, and audit readiness in all customer-facing quality activities; ensure traceability from conclusions to evidence.
Drive continuous improvement to CQE processes (FA prioritization, tracker hygiene, readiness documentation, lessons learned) and influence adoption across teams and sites.