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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 in 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. Our team is part of Azure Data, building reliable, large-scale distributed systems for data engineering. We develop Fabric Materialized Lake Views, which automatically refresh analytical data in Microsoft Fabric so customers can query up-to-date results without manual pipelines. We also maintain Azure HDInsight in production, the PaaS platform running open-source Hadoop, Spark, HBase, and Kafka.
Job Responsibility:
Write extensible, maintainable code in C#, Java, Scala, or Python for Fabric Materialized Lake View services and HDInsight components
Use AI tools and coding best practices across the development lifecycle
Design data refresh, scheduling, and query optimisation features with minimal supervision
Review code from teammates for correctness, test coverage, security risks, and adherence to team standards
Coach junior engineers through code reviews
Debug complex issues in distributed systems running on Azure, Linux, and Windows
Run live site operations on a rotational, on-call basis
Integrate logging and instrumentation to gather telemetry on system health, performance, reliability, and security
Work with product managers, technical leads, and partners across geographies to define customer requirements for Materialized Lake View features
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience
Experience with the Azure stack including Storage, Compute, Networking, Fabric, Purview, Synapse, AKS, DevOps, Data Factory, or Power BI
Experience with big data technologies such as Spark, Kafka, Hadoop, or HBase
Experience building data lake or data engineering products, tools, or pipelines
Familiarity with container-based architectures (Docker, Kubernetes)
Ability to debug complex distributed systems on Linux and/or Windows platforms
Nice to have:
Master's + 4 years technical engineering experience
OR Bachelor's + 5 years technical engineering experience