Software Engineering IC2

Contribute to Windows Fundamentals metrics, queries, cohort definitions, and measurement workflows across reliability, performance, responsiveness, power, battery life, memory, and storage. Develop, test, and maintain well-scoped components of backend services and data pipelines for telemetry ingestion, transformation, orchestration, storage, monitoring, diagnostics, and engineering workflows. Apply sound engineering practices for service reliability, security, compliance, observability, data quality, deployment safety, and operational support. Analyze telemetry, diagnostic signals, and traces, with support from experienced engineers, to identify trends, anomalies, regressions, and customer impact. Investigate data and service issues using debugging, statistical, and performance-analysis tools; document findings and contribute to engineering actions. Build automation, dashboards, alerts, and diagnostic workflows that detect issues earlier and reduce manual engineering effort. Collaborate with team members and partner teams, participate in design and code reviews, and continuously develop technical expertise in services, data engineering, and Windows Fundamentals. Bachelor's Degree in Computer Science, or related technical discipline with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Candidates need at least one year of software engineering experience. A bachelor's degree in Computer Science or a related technical discipline, or equivalent practical experience, is also required. Experience gained through coursework, internships, projects, or professional work in software development, backend services, data engineering, debugging, analytics, or related areas. Understanding of software engineering fundamentals, including testing, code quality, maintainability, data structures, and basic service or data-pipeline concepts. Solid programming, analytical, debugging, and problem-solving skills; ability to learn new technologies, incorporate feedback, and use data to support decisions. Coursework, internship, project, or professional experience with distributed services, cloud platforms, data pipelines, operating systems, or large-scale analytics. Familiarity with telemetry, metrics, SQL or KQL, data visualization, statistical analysis, performance engineering, or Windows internals. Exposure to service monitoring, data-quality validation, automation, machine learning, or AI-assisted engineering workflows. Experience collaborating on team projects and communicating technical ideas clearly. C, C++, C#, Python, PowerShell, and SQL/KQL; WinDbg, Windows Performance Analyzer, and ETW; Kusto, Azure services and data platforms, orchestration and monitoring systems, Power BI, statistics, experimentation, anomaly detection, machine learning, and AI-assisted analysis.