The interview process consists of seven steps, including the TA 1:1 meeting, but not including any contact with the hiring manager – or none that was offered to me.

Each stage is designed as a knockout round, as it evaluates just one competence. Candidates are eliminated if they are evaluated by the interviewer as "unsatisfactory." The potential for bias here is enormous, as there is no structure, panel, or holistic evaluation.

The role was described in great detail as an analytical engineering role, aspects of which I was eager to discuss. However, the first two competence assessment stages focused almost exclusively on insights delivery. During the second assessment, I asked the interviewer if they could expand a little on "a week in their role," as I had only the job description to go by thus far, not having met the hiring manager, and was becoming somewhat confused about the role's function.

They presented what was effectively a generalist BI role, and any question regarding analytical engineering topics (version control, pipeline testing, etc.) was answered with, "It is in our plans, but we are not there yet." I shared that I applied for the role understanding it to be an analytical engineering role, and up to that point, there were more hints that this was a BI role, which was not what I expected or what I am interested in pursuing. The interviewer then shared that AE activities would make up about 80% of the time.

Two days later, I received communication from the TA partner stating that despite positive assessment results, I would not be a good fit for the role because I am too interested in the analytical engineering part, which, according to the hiring manager, would be at most 50% of the role. The rest would be comprised of supporting business stakeholders with analyses, insights, and reporting.

Sadly, there seems to be a trend for companies to misappropriate the "analytical engineer" role to simply rename traditional BI responsibilities, adding none of the extended ones brought by the advent of the modern data stack. They still expect data professionals who apply to these engineering roles to effectively function as data generalists. In this market, many may swallow the pill, but many do so also because, in the beginning, they were drawn by deceptive titles and job descriptions. It is quite sad to notice this trend on both sides of the ocean.

Describe a past project that has had an impact on the business.