There was no interview experience for this role on the forum, so I am sharing mine. From the job description, this role looks like an analytics engineer plus a product analyst. With the impact of AI, one person really can do all of this work.
Process:
After a friend referred me, the recruiter reached out.
Online assessment: six or seven SQL questions, not hard. I passed.
HM interview: the HM seemed to be in a hurry and barely looked at me. They asked what big-impact work I had done using AI.
Technical interview: it was not hard. There was one very simple SQL question, which as I remember was just a window function. The Python question was not hard either; it was an especially simple loop. But before those, they tested the data-ingestion work expected of an analytics engineer. I had to use JSON to connect to an API. I had never learned that, so I failed...
They were all very simple questions, so failing felt a little unfortunate... It also made me think:
As AI develops, people's ability to learn has improved significantly. At least that is true for someone with straightforward ADHD like me, because lowering the difficulty of finding information lets me learn quickly from material that has already been summarized. So I predict the trend will be toward more hybrid, general roles. The range of required skills will keep growing, companies will expect more, interviews will get harder, and they will cover more ground. But because of AI, these roles do not actually need requirements this high. You just need one person who knows how to do prompt engineering. So maybe there is no need to take these interviews too seriously? I also happened to see a discussion in a job-search group saying that cheating in technical interviews is becoming more serious. I feel that I studied seriously but, through bad luck, did not interview well, and it seems a little not worth it.
What do the experts on the forum think?
Discussion
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