After recruiter outreach, I went through a structured set of rounds built around speed and clear problem solving. The recruiter call covered role fit and process details. Then came a technical screen with several SQL and Python tasks under tight time limits. I had to keep working until each task was fully resolved with the expected results, while the interviewers kept returning to my thought process and, where relevant, time complexity. SQL and Python were tested through joins, aggregations, window functions, and data-structure-style coding. The hard part was the pace. There was little room to debug slowly.
If I got past that first hurdle, later rounds focused on connecting product thinking to data work, communication, and behavioral judgment. I had several deeper SQL and Python rounds plus product scenarios about defining success metrics, designing a data model, and writing queries for those metrics. The modeling work put the most pressure on me because I had to explain why I chose an approach and how I turned a product goal into the right schema and joins. Situational behavioral discussions covered production issues and conflict, with an emphasis on decisions under pressure.
By the end, feedback often centered on how quickly I could communicate and reason with little room to recover from mistakes. In some cases the process paused for internal reasons before the final stage; in others I did not make it past the technical screen or later rounds. What I remember most is how strongly the process rewarded fast, structured thinking. When I could not complete every required step or had pacing issues, it clearly hurt my chances.
Location: Singapore. Overall feedback: neutral. Offer status: no offer.
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