Software Engineer 2(SWIQ Performance team)

Build services, tools, and automation that improve the efficiency and reliability of large-scale telemetry and data platforms. Investigate storage and compute optimization opportunities across Azure Storage, Cosmos, and Blueshift and help drive them into production. Develop dashboards, analytics, and recommendation tooling that help engineers understand usage patterns and identify savings opportunities. Work with partner teams to validate opportunities, implement improvements, and measure business impact. Apply AI-assisted engineering tools and automation to improve investigations, analysis, and operational workflows. Contribute to system design, implementation, testing, monitoring, and ongoing service 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 These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Experience building backend services, cloud applications, data pipelines, or distributed systems. Solid problem-solving skills and an ability to analyze complex technical issues using data. Experience working collaboratively in a team environment and driving projects to completion. Interest in cloud infrastructure, data platforms, automation, and AI-assisted engineering practices. Experience with Azure Storage, Blob Storage, or storage lifecycle management. Experience with Kusto (KQL), Cosmos, Spark, or large-scale telemetry systems. Experience using data analytics to identify performance, reliability, or cost-efficiency improvements. Experience with AI-powered development tools, automation frameworks, or intelligent operational tooling.