Octane Interview Questions
& Process

I went through six rounds of interviews, plus a take-home scripting project. The first two rounds were good, but as the process went on, it got really frustrating and disorganized. Later interviewers, even senior folks, asked stuff that seemed unrelated to the role and sometimes they weren't clear on things. Like, I talked about ESXi and VMware, and then got asked random questions about CPU architecture instead of virtualization. And when talking about network segregation, they said VLANs weren't needed and subnets alone were enough, which isn't best practice for on-prem with physical firewalls. Then, for SAML SSO, they wanted to know the deep backend workings and internal architecture, which felt unreasonable for this role, like you'd only need that if you were building SAML itself. Overall, the interviews became unrealistic, inconsistent, and a waste of time. It would be better with clearer role expectations, more relevant tech talks, and better interviewer alignment.

The interview process was pretty fast once we connected. Although the position was backfilled, it took them about a month to get back to me. It was basically two main steps: First, a recruiter screen and a hiring manager chat back-to-back. Then, a final round that included the recruiter and HR, followed by the engineering manager, then an engineer, and finally two product directors. In total, it was about 4.5 hours of interviews. For anyone concerned about DEI at Octane, it's something to consider here, more so than elsewhere. Looking at their leadership structure will give you an idea why.

The job was for a software engineer role with a focus on data engineering. Initially, I had three interviews: a live coding session using Python (one question), an HR/culture-fit interview, and a SQL test with several short questions. I had the choice to do them all in one day or spread them out. After those, I had an unexpected but welcome additional interview with the hiring manager, which gave me more time to discuss the role and my background with another team member. The whole process was very efficient and quick, which I really appreciated. The team was very communicative throughout and made me feel extremely welcome. I thought they were all highly competent and would be great colleagues. I'd definitely recommend applying here based on my experience. I ended up declining the offer because I got a better one, but I would't have hesitated to accept this one if it was my only option. It was tough to choose because they made such a strong positive impression. There was a bit of a red flag, though, with inconsistent information about location-based pay. The HR manager mentioned a *specific* salary increase if I moved to New York, which I'd indicated I planned to do. But when I tried to negotiate to match my other offer, I was told the location-based increase was actually performance-based after moving, and nothing was in writing. Given I'd be moving in less than 1.5 months, I wasn't sure how performance could be assessed so quickly. Plus, I'm confused why one person gave an *exact* figure and a senior person said it was performance-based with no exact number. Even so, the offer was still good, and I would have been happy with it if my other offer hadn't been higher. If you're planning to move to New York, I'd suggest being super clear about your moving timeline to ensure it's discussed properly. In my case, I was going to sign a lease within 3-4 weeks of accepting, and I didn't make that clear enough, which affected the offer (lowered it since I wasn't there yet). Another company offering 'New York pay' beat it by over 15%.

VP Talent reached out, remembering me from 10 years ago for a different company. First interview with the hiring SVP, then two interviews focused on coding, basic data science, and business analysis. After that, two more interviews on data science and business strategy. Finally, I interviewed again with the hiring manager and the CRO. The interviews heavily emphasized coding and modern data science principles. While not overly difficult, the questions were very specific, and pseudocode was acceptable, though Python was strongly preferred.