Know the data lakehouse concept cold — it's the foundation of everything Databricks does
Databricks is built by academics turned entrepreneurs who care deeply about technical excellence. The culture values intellectual honesty, deep technical knowledge, and a genuine passion for the data and AI ecosystem.
Explain the difference between a data warehouse and a data lakehouse.
How would you design a scalable real-time data processing system?
Tell me about a complex data engineering project you've led.
How would you explain Apache Spark to a data analyst with no engineering background?
What's the future of data infrastructure in your view?
Understand Delta Lake, Apache Spark, and MLflow — Databricks' core open-source projects.
The data lakehouse vs data warehouse debate is central — have a strong, informed opinion.
Databricks is enterprise-focused — understand how data teams make buying decisions.
The academic culture means depth matters more than breadth. Go deep on what you know.
SQL, Spark, and Python are the most common technical areas evaluated.
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