At this level, individuals have a basic understanding of the Databricks platform and its components such as Apache Spark, Databricks notebooks, DBFS, and clusters. They are aware of the functionalities these components provide but may not have hands-on experience with them.

Novices can perform simple tasks in Databricks like creating and managing clusters, running jobs, using notebooks for data exploration, and reading/writing data using DBFS. They can also perform basic data transformations using Spark DataFrames. However, their understanding is still limited and they may need guidance.

Intermediate users can optimize Databricks jobs for performance, manipulate data using Spark SQL, integrate Databricks with external data sources, schedule and automate jobs, and implement ETL pipelines. They have a good understanding of the platform and can work independently on common tasks.

Advanced users can design and implement complex data processing workflows, tune Spark applications for performance, secure Databricks enviroments, integrate it with other cloud services, and build machine learning models. They have a deep understanding of the platform and can handle complex tasks and troubleshoot issues.

Experts can architect large-scale data processing solutions, deeply understand Spark internals for optimization, implement advanced machine learning algorithms, develop custom extensions and integrations, and lead and mentor teams. They have a comprehensive understanding of Databricks and can handle any task or issue that arises.