Job Description:
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 big data analytics team provides a range of products that enable data engineers and data scientists to extract intelligence from all data – structured, semi-structured, and unstructured. We build the Data Engineering, Data Science, and Data Integration pillars of Microsoft Fabric. The Fabric Spark team is looking to push the frontiers of analytics performance and scale. You will have to help rebuild the way analytics engines process data. We build services that enable big data developers to build mission critical applications with high levels of SLA through auto detection and healing. We enable advanced data Insights and recommendations externally to our customers. As a Software Engineer II on our team, you will have an opportunity to work on and extend OSS technologies like Spark, Gluten, Velox, Delta and Hadoop as well as proprietary Microsoft services. You will help design & implement software components, participate in code reviews, design reviews, assist customers as needed to be able to leverage the service and keep the service running. You will work with a team of talented engineers aiming to solve performance issues by looking at an entire workload and learning from its execution history. Your goal is to make onboarding new workloads on to Fabric a breeze and to help keep them continuously tuned with changes in the Spark engine and user workload. This will require exploring the frontiers of what is possible. You should be AI forward in your approach to delivering impact.
