Anthropic Data Engineer Interview Guide

{"experience":"The process started with a Coderbyte OA, and that was probably the cleanest part of the whole thing. I cleared it by solving both hard questions, one centered on a hashmap and the other on graphs, and then got invited to the first onsite round. After that, the experience got a lot messier than I expected. I had a recruiter screen and an engineering manager screen, followed by three technical rounds covering SQL, Python, and system design. The SQL round focused on window queries, the Python round was about priority queues and min-heaps, and the system design round asked me to design a wallet payments flow. The technical questions themselves were not wildly exotic, but the interviewers were not always clear, which made things harder than the actual content should have been. One thing that stood out was how much the execution issues affected the process. I was emailed and called by the wrong name multiple times, one interviewer no-showed and I ended up waiting around for 45 minutes, and the reschedule got pushed again at the last minute. On the coding side, I also had a frustrating moment where my solution logic was right but my code didn’t run successfully because I didn’t convert a time string into the right numerical format, so none of the test cases passed even though the problem itself was pretty easy to reason through. Overall it felt unprofessional and disorganized, and I was eventually rejected. outcome":"No offer outcome_color":"red prep_tip":"Be ready for SQL window-function questions, plus Python problems involving priority queues/min-heaps. For the coding round, pay close attention to input parsing and type conversion, since a simple formatting mistake was enough to sink an otherwise correct solution."}