About the role
* 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. Produce code with few defects and clear test coverage. Design data refresh, scheduling, and query optimisation features with minimal supervision. Evaluate design options, document trade-offs, and begin owning or co-owning the architecture of Fabric data engineering components. Review code from teammates for correctness, test coverage, security risks, and adherence to team standards. Coach junior engineers through code reviews and provide feedback that raises code quality across
the team. Debug complex issues in distributed systems running on Azure, Linux, and Windows. Use debugging tools, logs, and telemetry to verify assumptions before issues reach production. Conduct incident retrospectives for Fabric and HDInsight services; identify root causes, implement repairs, and prevent recurrence. Run live site operations on a rotational, on-call basis. Diagnose and fix both simple and complex issues across Fabric and HDInsight workloads. Improve troubleshooting guides, tests, and telemetry to make on-call better for
the team. Integrate logging and instrumentation to gather telemetry on system health, performance, reliability, and security. Classify metrics, build dashboards, and create alerts that surface problems across the Materialized Lake View pipeline. Work with product managers, technical leads, and partners across geographies to define customer
requirements for Materialized Lake View features. Incorporate customer feedback into designs. Understand and advocate for the security and privacy needs of customers. Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, Apache Spark, Kafka, Spark SQL, PySpark, C, C++, C#, Java, JavaScript, or Python; OR equivalent experience. Master's + 3 years technical engineering experience; OR Bachelor's + 5 years technical engineering experience; 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.
