Software Engineer II - Fundamentals

Define meaningful Windows Fundamentals metrics and success criteria for reliability, performance, battery life, and sustainability. Analyze fleet telemetry, diagnostic signals, and traces to identify trends, anomalies, regressions, and customer impact. Build reliable data pipelines, queries, dashboards, and automated analyses that make device-health insights timely and actionable. Investigate metric movements using statistical methods, experimentation, debugging, and performance-analysis tools. Design, implement, and test well-scoped operating-system or analytics improvements that address identified opportunities. Evaluate data quality, establish baselines, quantify tradeoffs, and validate outcomes against measurable goals. Collaborate with Windows engineering, data science, security, servicing, Original Equipment Manufacturer (OEM), support, and enterprise partner teams to drive Fundamentals improvements. Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. OR equivalent experience. Bachelor's degree in Computer Science or a related technical discipline and 3+ years of software engineering experience - or equivalent practical experience. 1+ years of experience in software engineering, systems analysis, debugging, performance engineering, data engineering, or related work. Experience analyzing telemetry or operational data to diagnose system behavior and improve reliability, performance, efficiency, or security. Experience developing, testing, and delivering reliable production software, data pipelines, metrics, or analytics. Solid programming, debugging, data-analysis, and problem-solving skills; ability to independently execute well-scoped work and use evidence to guide decisions. Experience with operating systems, system-level development, performance engineering, data engineering, or large-scale analytics. Knowledge of Windows internals, reliability engineering, performance analysis, or power efficiency. Experience defining KPIs, establishing baselines, investigating regressions, and communicating insights through dashboards or technical reports. Experience with Kusto, Azure data platforms, fleet telemetry, statistical analysis, experimentation, anomaly detection, or machine learning.