Real Interview Experiences
Learn what to expect directly from candidates and interviewers who've been through it.
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“What stood out to me is that every loop round started with product sense, then I had to turn that answer into a data model, and from that they jumped straight into SQL and Python. One case was even an Instagram metric drop where I had to do root cause analysis live.”
“Overall: The interview was well structured and closely matched the role. It covered SQL and BigQuery performance, dbt pipelines, data modelling, Airflow, data quality, Python, debugging, cost, and cloud platforms. The scenarios were realistic for an attribution-pipeline migration, which made it a good test of practical skills rather than theory. What went well: The questions were scenario-based and relevant: late-arriving attribution data, restated ad-network spend, backfills, and duplicate investigation. The interviewer followed up on my answers and rephrased or repeated questions when I asked, so I could go deeper. The pause option and the freedom to take time to think were helpful. I felt strongest on dbt pipeline design, data quality testing and investigation, and data modelling for marketing data. What didn’t go well: In the data quality section, the screen kept showing questions from earlier sections while new ones were asked by voice, and the check-in question was repeated several times. This broke my concentration for a while. The suggestion to turn away from the screen was confusing, because the questions were displayed on that same screen. The session ran about 10 minutes over the scheduled time. On my side, a few BigQuery-specific questions, such as partition pruning behaviour and query plan metrics, deserved sharper answers. I’ve since reviewed those topics. There was no opportunity to ask about the team or the project, which I’d normally do with a technical lead.”
“The interview was mostly technical. And almost all the questions were focused towards Databricks. for the cloud stack, mostly focused on AWS.”
“It was a video interview but the interviewer did not turn on his video. It was completely technical fully focused around Databricks.”
“IT was a AI based interview, where the interviewrs asked me some technical question related to spark, partitons, How did i managed a end to end data pipeline, how did si deploy data infrastructure”
“all went well, no problem at all, everything was smooth. interviewr was nice & soft spoken. Team was nice”
“Interviews are aligned with what mentioned in the Job description. Expect some system design questions as well. ”
“The overall interview process was incredibly smooth, straightforward, and well-organized from start to finish. The recruiter was exceptionally friendly, responsive, and did a fantastic job of setting clear expectations for each stage. There weren't any significant downsides, as the scheduling was efficient and the communication remained consistent throughout.”
“I definitely had good preparation on LP question which is one of the most important area because company focuses on this a lot”
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“The weirdest Anthropic round was the company values interview. It was almost like a therapy session, and honestly if you went to a therapist at some point, you will pass that round much more easily.”
“What was very unusual is they didn’t give me any tooling to draw the system design, so I just sketched it on a piece of paper and talked them through it, then we got into this oddly deep debate about whether hover-over history should count as a recommendation signal.”
