Join the Windows + Devices Fundamentals team to build and manage data platforms and backend services that enhance Windows performance, power efficiency, and reliability. This role focuses on connecting signals from labs and the user base to create trustworthy metrics, actionable diagnostics, and measurable improvements in areas like responsiveness, battery life, and device health.

You will lead a data and services product area, overseeing the entire lifecycle from problem identification to delivery and continuous improvement. Collaboration with engineering, data science, and partner PMs is key to ensuring data trustworthiness, service usability, and actionable insights. The position blends hands-on analysis with strategic product ownership, requiring you to ask insightful questions, define clear requirements, and drive impactful results.

Microsoft is dedicated to empowering every person and organization globally to achieve more. We foster a culture of growth, innovation, and collaboration, guided by values of respect, integrity, and accountability. We are committed to building an inclusive environment where everyone can thrive.

Take ownership of a feature area by understanding user needs, defining clear problem statements, requirements, and success metrics, and prioritizing tasks within the team's roadmap.

Define and analyze key metrics, conduct investigations using SQL/KQL to understand product health, and collaborate with data science and engineering to interpret results and distinguish between genuine regressions and data anomalies.

Enhance data quality by partnering with engineering on instrumentation, schemas, and pipeline requirements, defining quality checks, and integrating privacy and security considerations.

Develop valuable service experiences by defining requirements for APIs, dashboards, and diagnostic workflows, and utilizing partner feedback to improve onboarding, documentation, and self-service capabilities.

Drive decisions based on fundamental metrics like responsiveness, memory usage, battery life, and stability, helping teams identify regressions and assess improvements across different device and silicon cohorts.

Ensure successful delivery by coordinating milestones, managing dependencies, and assessing risks, working with engineering on safe rollouts, release criteria, and monitoring.

Continuously learn from operations by tracking adoption, data quality, and service health post-release, prioritizing improvements based on feedback and operational findings.

Communicate effectively by explaining findings, progress, and trade-offs to partner teams, documenting decisions, and fostering an inclusive, collaborative environment.

A Bachelor's Degree with a minimum of 2 years in product, service, or program management, or software development, or equivalent experience is required.

Additional qualifications include the ability to meet Microsoft, customer, and government security screening requirements, including a Microsoft Cloud Background Check.

Preferred qualifications include a Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. A minimum of 3 years in product management, program management, software engineering, data engineering, or a related technical role is also preferred.

Experience in defining and delivering data, analytics, or service features with engineering partners, including setting requirements and success measures, is beneficial. Proficiency in SQL, Kusto Query Language (KQL), or similar tools for data analysis is expected.

A solid understanding of data pipelines, APIs, and service health metrics, with the ability to translate technical findings and customer feedback into actionable requirements, is crucial.

Foundational knowledge of performance, power efficiency, or reliability, and their impact on customer experience, is advantageous.

Experience with telemetry, diagnostics, dashboards, or experiments for problem identification and improvement evaluation is a plus.

Familiarity with Kusto, Azure, or comparable cloud platforms, monitoring, and service-level objectives is preferred.

Experience with Windows, operating systems, devices, or applications where responsiveness, battery life, and stability are critical is desirable.

Collaboration experience with engineering and data science on data quality, privacy, or security requirements is beneficial.

Exposure to statistical analysis, anomaly detection, automation, or AI-assisted diagnostic workflows is a plus.