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Pure Hadoop administration is fading, but Spark, Hive, and the broader distributed-processing concepts it teaches remain directly transferable to Databricks and cloud-native pipelines, so learning it alongside Spark on a cloud platform is more useful than learning it in isolation.
The most common path is picking up a cloud platform (AWS EMR, Azure Databricks, or GCP Dataproc) on top of existing Spark skills, since service companies like Cognizant and Capgemini actively move Hadoop-experienced engineers onto cloud migration accounts rather than hiring fresh for those projects.