Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world.
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.

​​​​Azure Cosmos DB is one of the fastest growing Azure services that provides globally distributed, low-latency, massively scalable, multi-model cloud database service. It is designed to enable developers to build planet-scale applications.
We are hiring a Senior Software Engineer to join the Azure Cosmos DB team, where you will be working on a large-scale distributed operational database. In this role, you will work on distributed systems problems and technologies to determine the future of our planet scale database.

The Cosmos DB MongoDB vCore team is making it possible for anyone running MongoDB to instantly scale across the globe, with guaranteed speed and reliability. Our work directly powers mission-critical apps from financial systems to e-commerce to healthcare without developers having to change a single line of code. Joining us means solving problems at hyperscale and shaping the future of cloud databases.