Speedy, intense, engaging, and challenging. The hiring manager reached out to me on LinkedIn directly and was my main point of contact throughout the process. He was supportive, had my back, and rooted for me to succeed.

Six rounds within two weeks:

• Screening round: With the hiring manager.
• Coding round (take-home): One week to complete 2 out of 3 assignments on the Databricks platform using PySpark.
• Architecture interview: With a Senior peer. Given a business use case of a customer trying to solve a data engineering plus predictive analytics problem, design an architecture for the workflow (whiteboarding).
• Technical interview: With a Senior peer. Expect to be grilled on every aspect of an ML project you have worked on, probing why you did what you did.
• Situational interview: The toughest one for me. A role-play situation where two managers and a peer play the role of a new customer, and you, as an SA of Databricks, make a tech pitch. You will get a slide deck to prepare and use your own ideas to present. They are interested in how you conduct yourself in such a situation more than the content of the pitch (they don't expect you to be a Databricks expert already).
• Executive interview: A senior exec will talk to you to understand your motivations for this role and explain their vision.
• Offer discussion: Lastly, came the talk about the offer with HR.

It all happened virtually for me. Easily the best interview experience I have had, and I have had quite a few!

Q: How would you get the data from the client's local FTP server to AWS S3?

Q: What is so random about Random Forest?

Q: How will you handle imbalanced classes in a particular classification problem?