Modern data platform choices now hinge less on “can it store and query data?” and more on how the platform behaves under enterprise pressure. Can analytics teams share the same data without copying it five times? Can BI run at business speed? Can costs stay predictable as usage grows across engineering, reporting, AI and governance workloads? Microsoft Fabric and Snowflake both answer those questions with mature cloud-native designs, but they take different architectural path

A senior Azure data engineering interview rarely tests syntax alone. The interviewer wants to know how decisions hold up when a pipeline fails at 2:00 am, a finance report is late, a Spark job runs out of memory, or a regional outage affects a data platform used across countries. Scenario-based questions reveal how well a candidate thinks about recovery, scale, cost, data quality, governance, and business impact. The best answers are practical. They explain the design, the tr