New 
Software Engineer II
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 23, 2025 | |
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OverviewMicrosoft's Commerce + Ecosystems (C+E) organization empowers all Microsoft businesses and third parties to bring their products and services to market across all channels and clouds. Within C+E, the Platform Data and Experiences (PDX)team's missionistoproduceaccurate, reliable, and efficient records of charge, empowercustomers and partners through insights and analytics, and elevatecritical commerce functions through code, data, models, insights, and email platforms. Aligned with this mission, the Programmability Insights & Engineering (PIE) team delivers critical commerce experiences through deep integration across charges, billing, and pricing platforms. We innovate in distributed data storage, intelligent routing, and scalable data modeling-powering a broad range of customer scenarios. Our work unlocks business value through advanced datamodels, leveraging enriched data stores, anomaly detection, and customer benefit insights. Join us to be part of a dynamic, inclusive team that values diverse perspectives, empowers individuals to drive meaningful change, and is shaping the future of data platforms. As a Software EngineerII onthe team, youwilldesign, build,andoperatescalable data pipelines thatrun Anomaly detection on Commerce Datasets such as Usage, Charges,Pricing, Invoices, Credits and Balances. We support commerce with a focus onreliability, security,andcorrectness.You'llapplythe latestAI-assisted engineeringtoolstoaccelerate problem solving and delivery, move with urgency, and balance speed with qualityandsafety.You'llgrow by seeking feedback, sharing ideas, and learning from diverse perspectives,livingMicrosoft's values ofrespect, integrity, and accountabilitysoeveryone can thrive.
ResponsibilitiesDesign, develop, and maintain Spark-based data pipelines on Azure Synapse for large-scale anomaly detection and reporting. Implement distributed data processing solutions leveraging Spark for batch and streaming workloads. Collaborate with product managers, data scientists, and engineering teams to deliver end-to-end solutions. Coordinating data domain teams to understand datasets and onboard them to Anomaly detection platform. Ensure data quality, integrity, and compliance across multiple sources. Optimize Spark jobs for performance, scalability, and cost efficiency in cloud environments. Contribute to code reviews, design discussions, and architecture improvements. | |