Tell me about your experience.

"The interview process spanned four rounds: an initial screening covering analytical puzzles, past project deep-dives, and situational consulting scenarios; a take-home assignment requiring an end-to-end Factory Copilot integrating computer vision for part defect inspection with a RAG pipeline over internal SOPs; a technical defense round reviewing the assignment's architecture, design trade-offs, and horizontal scaling strategies; and a final hiring manager round focused on behavioral fit and employment history, where I was ultimately rejected over behavioral questions and the handling of career gaps."

"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."

"I was allowed to use AI for the first screening technical interview. Still interviewing with the rest of the team, but the rest of the interviews (System Design, 2 coding interviews, Project retro, and behavioral)."

"Very fast paced and quick answers expected. A lot of metrics calculations. Focus on explaining what concepts you learned in your past projects."

"The interviewers were really nice and guided me though the questions. for the coding part I managed to find the optimal solution, for the sys design they walked me through"

"Process was straightforward and covered basic resume review. ASked about design experience and UX background"

"all went well, no problem at all, everything was smooth. interviewr was nice & soft spoken. Team was nice"

"The whole process was really fast for me, about three weeks end to end, and the ads org was super snappy about scheduling and responses. The recruiter reached out because my background lined up with what they want, and it felt obvious from the start that this team cares a lot more about ads domain fluency than generic big tech interview performance. I had a recruiter screen, a TTL cache phone screen, and then a five-round onsite with one coding round, two behavioral EM rounds, data modeling, and system design. The technicals were mostly straightforward if I could talk through tradeoffs, but the behaviorals were a much harder vibe check than I expected. I am still waiting to hear back, but the biggest thing I took away is that if I can speak confidently about how ads serving, demand, targeting, and capping actually work, they will forgive more than they would at other companies."

"Barely gotten experience with system design interviews, that one threw me off my game and after it I got the business case. I was too nervous after the system design interview that I fumbled both"

"The interview process was well-structured and included both technical and client interviews. The technical discussions focused on my experience with Power BI, data modeling, SQL, and real project scenarios. Overall, the interviewers were professional and gave me enough time to explain my approach. The only downside was that the feedback process took longer than expected, and communication between interview stages could have been more consistent."

"I interviewed for a Product Manager role at Coinbase after getting in through a referral. The process started with a very short recruiter screen, then a high-level hiring manager conversation where I mostly walked through my resume and background. After that, I had a super round with five case-based interviews covering success metrics, product design, a card-usage drop-off case, improving a product I like, and wireframing improvements for the Coinbase trading dashboard. Honestly, the structure felt pretty standard and not especially difficult, and I felt like I nailed the interviews. What was frustrating is that I made it to the final round, asked for feedback, and still never heard back."

"The process was very simple but very unorganized; the interview got postponed once. I would say it would have been better if we knew what kind of questions they were about to ask, at least domain-wise, as the final round was more behavioral but not well done."

"It was ok, the interviewer was barely able to speak english well. I couldn't understand what she was saying and had to ask her to repeat many times. I even offered: "We can speak in Mandarin if needed" and the interviewer insisted in speaking in English."

"Not a hard process. Just communicate clearly. Must talked in a structured approach and take your time."

"The process was bit lag but being patient wins the race. Be confident, explain deeply on your experience, work that uniquely done, times you have gone above and beyond. How you uplifted the team and delivered"

"Behaviour heavy. Prepare for typical product manager interview questions, I woulnd't say the questions are too challenging."