Disclaimer: I'm fully aware of the previous experiences that other candidates have reviewed for this role, and I appreciate that DB was probably in a different stage compared to the present, thus explaining why there were more negative-skewed reviews.

The interview process for the SA role at DB was straightforward, well-organized, and completely respectful from my perspective, especially since I managed expectations from the very start that I did not come from a Data Science/AI/ML background.

While there were many stages in the process compared to other organizations I've interviewed with, I felt completely comfortable and enjoyed each interaction. The lead recruiter also did a fantastic job in keeping me up-to-date and prepared me accordingly for each stage:

• Recruiting Sourcer from LinkedIn (30 min call)
• Lead Recruiter Screen (45 min call)
• Hiring Manager Screen (45 min call)
• Take Home Technical Assignment (1 week deadline)
• Technical Interview: Architecture & Data Science/Engineering Questions (1 hour)
• Presentation (Pre-Sales) Showcase (30 min prep call with HM and 1 hour call for presentation)
• Executive Leadership Interview (30 mins call)
• Hiring Manager & Lead Recruiter Wrap-Up (30 mins)

Potential candidates may see the above as long-winded, but if you're serious about joining DB and you are worth your weight, then these stages should be effortless. After all, would you join a company which has subpar employees? Probably not.

DB has also done a tremendous job in streamlining/parallelizing these stages, so it took approximately 3 weeks to complete (as opposed to 8 weeks from other reports) until a formal offer was extended and accepted.

Standard screening questions cover your current role, career experience, Databricks as a product/company, and reasons for seeking a new role.

While an NDA was signed for the technical assessment (preventing the sharing of specifics), it involved solving a series of questions using a Databricks cluster and notebook. You should encounter no problems answering as long as you can read API documentation and reference answers found via Google/Stack Overflow.

The technical interview rounds included describing a solution architecture you've implemented, the business challenge it solves, potential areas for improvement, and more general questions on Spark, ETL, and data engineering.

The sales presentation round extended the technical interview by simulating the proposed solution to a customer, including objection handling and demonstrating business acumen. For example, you might be asked: 'Why have you proposed this solution, and how does it address our business needs?' or 'We already have X, why should we use this?'