went through the full process for a senior data engineer role on the QuickBooks data platform team. figured i'd write it up while it's fresh.
Round breakdown: recruiter screen: 30 min, pretty standard. talked about scale, my pipeline experience, rough comp range. recruiter was sharp and moved fast. technical phone screen: CoderPad, 45 min. one medium SQL problem (window functions, find customers with consecutive months of inactivity), one Python/pandas question. not hard, but they time you on the SQL. virtual onsite: 4 panels over one day data modeling: design a transaction enrichment pipeline for financial data. latency vs. cost tradeoffs, partitioning strategy. coding: graph traversal problem. straightforward if you've done any LC mediums. behavioral x2: both interviewers asked about customer-obsession stories, one asked about a time you dealt with bad data in production and the downstream impact.
What surprised me: they asked very specifically about how you handle data quality issues that could affect a customer's tax filing. not generic "tell me about a data quality problem". the financial domain specificity was real.
What I'd prep: know your SLAs, know what downstream consumers your pipelines fed, have a story about catching something before it caused a customer-facing problem.
Got an offer. total process was 3.5 weeks from recruiter reach-out to offer call.