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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 emergence 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 Data Engineering Experience & Infrastructure team is hiring to help build world best Data Engineering and Data Science platform. You will help implement advanced capabilities designed to help Data Engineers and Data Scientists to achieve more through Microsoft Fabric.
Job Responsibility:
Design and develop world-class experience for new big data cloud offering
Plan, schedule and deliver quality software incrementally
Review changes to product codebase and provide constructive feedback that align with industry practices
Maintain and operate cloud online services
Passion and experience for building powerful developer experience and user experience of modern analytics systems
Have a deep desire to work collaboratively, solve problems with teams across the world and celebrate successes
Requirements:
Bachelor’s degree in computer science, or related technical discipline AND substantial experience in industry software engineering experience
Substantial experience in programming as data scientist
Software development experience building Machine Learning and Data Science platforms, including model training, experimentation, evaluation, and deployment workflows (e.g., experiment tracking, model registry, feature management)
Hands‑on experience with machine learning lifecycle management, including CI/CD for ML, model versioning, reproducibility, monitoring, and rollback strategies in production environments
Familiarity with modern machine learning frameworks and libraries, such as Mlflow as a plus
Experience with building on top of cloud platform like Azure/AWS/Google Cloud as a plus
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
Familiarity with modern machine learning frameworks and libraries, such as Mlflow
Experience with building on top of cloud platform like Azure/AWS/Google Cloud