Oura Data Engineer Interview Questions
& Process

The interview process was a mixed bag. It started great with a professional HR email and an easy-to-use booking system. The HR interview went well, lasting about an hour. It felt like a startup environment, which might not be for everyone expecting big company structure. The HR person said the next interviews would be technical, covering both high-level and deep dives into expertise. But honestly, the next interviews didn't feel that different. The team interview, with team members, was about 1.5 hours. They had a list of questions and went through them. Topics included databases, Spark, data quality, data warehouses, data lakes, and basic ML. It seemed like a good fit at that point; the team seemed really into their work. The next day, I got an invite for a manager interview. Then, a whole week passed with no news, which was a bit annoying since they didn't give a timeline upfront. Finally, I got an invite for a two-hour interview described vaguely as 'background and experience.' Surprisingly, about 70% of it was deep Python questions, like how Python is built and its modules – stuff that felt more like a software dev interview. Even though it was a data engineering role, they were looking for someone to optimize Python code. It seems they want one person to do it all: data engineering, cloud (AWS), advanced software dev, and ML/MLOps. Good luck finding that unicorn.

The recruiter was very communicative. We had 5 rounds in total: first a recruiter call, then an interview with the hiring manager, followed by rounds for System Design, Data Aptitude, Behavioral, and a Technical Screening.

This was a super fast process, took about 4 weeks because they really needed to fill the role. It kicked off with a quick chat with the recruiter. Then, there was a 1-hour coding interview that involved typical Python data wrangling and Hackerrank-style problems. After that, I had roughly three more rounds with managers and leadership. The whole experience was pretty good, and the interviewers were nice and helpful. Sometimes communication was a bit slow, which they mentioned was due to the high hiring volume and not enough recruiters.