Software Engineer

Microsoft’s Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture. Within Azure Data, the databases team builds and maintains Microsoft's operational Database systems. We store and manage data in a structured way to enable multitude of applications across various industries. We are on a journey to enable developer friendly, mission-critical, AI enabled operational Databases across relational, non-relational and OSS offerings. As a Software Engineer, you will have the opportunity to wear multiple hats to demonstrate breadth, depth, and leadership. Placement and load-balancing is a complex and highly sensitive area where even one change in the algorithms and policies can have immediate and impactful changes to customer experience as well as the economics of the business. Close ties with Microsoft Research mean that this position will afford opportunities to make externally visible research impact. We are looking for someone to help determine and build the next generation of algorithms and software for this crucial area of Azure SQL DB. The team's work focuses on cluster orchestration, usually a part of the “control plane” of cloud systems, and, is related to SQL DB’s tight integration with Microsoft’s Service Fabric cloud orchestrator (the same class of system as Kubernetes). Service Fabric is an orchestrator used internally and externally for the smallest next-gen container microservices, to the multi-billion dollar business that is Azure Data. The problem at hand is broadly a distributed systems problem as well as a pure search and constraint solving algorithms problem. The successful candidate will need an eye towards designing and building a high performance, highly reliable, search and constraint solver that will stand the test of time (years and years). The complexity of the component interaction graph and dependencies that are taken on this search optimizer (placement and load balancing) are substantial but justified due its mission critical nature.