My suggestion is to keep the path simple in the beginning. Start with SQL, basic Python, and core data engineering thinking first. Then learn Spark basics, DataFrames, transformations, and Delta Lake. After that, move into Databricks Lakehouse concepts, Unity Catalog, jobs, pipelines, and basic troubleshooting. Do not try to learn everything at once.

For practice, start with small projects like sales data pipelines, customer orders cleaning, inventory analysis, or simple streaming use cases. The goal is not to build something huge. The goal is to understand how data comes in, how it gets transformed, how it is stored, and how it becomes useful.

To become job-ready, focus on SQL, Python, PySpark, Delta Lake, data modeling basics, pipeline thinking, and a little governance and orchestration. If you stay consistent and practice regularly, you will build confidence much faster than you think.

You already have the most important thing, which is motivation. Now just follow a clear roadmap and keep building step by step. Wishing you the very best in your Databricks journey.