Principal Engineer, Validation Data Platform
The Validation Data Platform Engineer owns the reliability, scalability, and operational excellence of the DC SSD Validation Control Tower, driving platform services, data integrations, observability, health automation, and trusted validation insights for global engineering teams. Main Responsibilities Define and evolve platform architecture, service boundaries, deployment models, and technical roadmaps for the Validation Control Tower.
Develop and maintain integrations using APIs, databases, events, MCP-based interfaces, and automated pipelines while preserving authoritative systems of record.
Implement scalable metric onboarding, RAG computation, drill-down navigation, notification, and operational intelligence capabilities.
Establish data contracts, validation controls, lineage tracking, freshness monitoring, and failure-handling mechanisms across validation health pillars.
Build observability, telemetry, dashboards, alerts, and diagnostics that improve platform reliability and operational decision-making.
Lead release engineering activities including automated testing, CI/CD quality gates, rollback mechanisms, and production-readiness validation.
Resolve platform and data-feed incidents through structured triage, root-cause analysis, corrective actions, and reliability improvements.
Partner with metric owners, BI teams, infrastructure teams, and source-system stakeholders to translate business intent into testable technical solutions.
Leverage AI-assisted tools, automation frameworks, and data-driven workflows to improve engineering productivity and accelerate analysis.
Apply AI technologies responsibly to generate actionable insights, improve observability, and reduce manual effort while maintaining data quality, security, and governance
Evaluate emerging AI capabilities and integrate validated solutions into the Control Tower platform with appropriate human verification and engineering judgment.
Minimum Qualifications / Experience Bachelor’s degree in Software Engineering, Computer Engineering, Data Engineering, Information Systems, or a related technical field.
Demonstrated experience owning or sustaining a production platform, data product, observability solution, developer tool, or business intelligence application.
Experience designing and supporting integrations across multiple systems, including authentication, schema evolution, monitoring, and data validation.
Strong software engineering capability in Python or a comparable language
Preferred Technical Skills Experience with enterprise dashboards, metric platforms, operational control towers, data observability, or reliability engineering.
Familiarity with REST APIs, MCP-based integration, cloud-hosted services, containerized applications, and infrastructure automation.
Experience with Jira, JAMA, Summit, Progeny, Power BI, or comparable engineering workflow and data systems.
Knowledge of SSD validation, qualification, lab operations, telemetry, test execution, or engineering program management.
Ability to apply baseline digital fluency and role-appropriate AI literacy to use AI-enabled tools responsibly and effectively for research, analysis, content creation, problem-solving, operational tasks, and achieving business outcomes.
Soft Skills Structured problem-solving and sound technical judgment.
Clear communication and cross-functional stakeholder management.
Ability to operate independently in ambiguous environments and drive execution to closure.
Technical leadership, mentoring, and influence without direct authority.
Embody Micron's Core Values People – Respect, develop and empower others
Innovation – Drive continuous improvement and breakthrough thinking
Tenacity – Show grit and determination
Collaboration – Build trust and foster teamwork
Customer Focus – Deliver excellence and value
Speed – Act with purpose and set the pace