Analytics Engineer applicants have rated the interview process at Shields Health Solutions with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 64.3% positive. This is according to Glassdoor user ratings.
Candidates applying for Analytics Engineer roles take an average of 30 days to get hired, when considering 2 user submitted interviews for this role. To compare, the hiring process at Shields Health Solutions overall takes an average of 20 days.
Common stages of the interview process at Shields Health Solutions as a Analytics Engineer according to 2 Glassdoor interviews include:
Phone interview: 33%
One on one interview: 33%
Skills test: 33%
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I applied online. The process took 4 weeks. I interviewed at Shields Health Solutions in Jun 2025
Interview
TLDR; I was transparent that I needed an offer of at least my current salary, which I disclosed, early on. I was dragged through a technical assessment and 6 interviews just to learn that they couldn't match that. They offered $115k+10% bonus.
Internal and external communication were very messy. The interviewing team was not on the same page, and the recruiter could not remember conversations we'd had and did not follow up when she said she would. When I brought this to the team's attention, they questioned my ability to work in a fast-paced environment, as if this is what I could expect working at Shields.
Interview questions [1]
Question 1
If you flip a coin 3 times, what are the odds you get heads exactly twice?
The interview process included four virtual rounds covering SQL, data modeling, stakeholder communication, and team collaboration. It was structured, thoughtful, and focused on real-world problem solving, technical skills, and alignment with the team’s collaborative and healthcare-driven environment.
Interview questions [1]
Question 1
One of the most interesting questions they asked was how I would handle matching patient records across multiple EHR systems — especially when a patient appears under different names or IDs — and how I’d validate that logic.