Went through Bain's DE loop last month for a role on their global analytics infrastructure team. They don't hire as many DEs as consulting firms hire analysts, so there's not a lot out there about this process. Here's what I found.
Recruiter screen: 30 min, mostly resume walk-through and the usual culture questions. They emphasized that Bain's analytics team is embedded with consulting teams, so you'll interface with a lot of non-technical people. Translation: communication skills actually matter here more than at a product company.
Technical round 1: SQL + data modeling Two SQL questions plus one data modeling prompt. SQL was solidly intermediate: a multi-step CTE to compute client-level churn, and a query to find the first and second purchase date per customer. The modeling prompt asked how I'd design a schema to track consulting engagement KPIs across multiple clients, each with different metric definitions. I drew an EAV variant and we spent 15 minutes arguing about it. They were testing how I'd reason under ambiguity, not looking for one right answer.
Technical round 2: Pipeline design + systems This one surprised me. They wanted me to walk through a real pipeline I'd built: architecture, failure modes, how I'd handle schema drift. Then they gave a scenario: a client's data lands in S3 every night but with no guaranteed schema. How do you build a robust ingestion layer? I talked through schema inference, contract testing, dead-letter queues. They asked good follow-up questions.
Behavioral: A lot of the same as the DS loop. Wanted a story about handling a data quality crisis under deadline. One question I hadn't prepped: 'what would you explain differently to a partner vs. an engineer?' Worth having an answer ready.
No leetcode-style algorithms at all, which honestly was refreshing. The SQL and design depth more than made up for it.
Total timeline: 5 weeks. Boston HQ role, 3 days/week in office.