Klaviyo Interview Questions
& Process

I interviewed for a leadership role. They ghosted me with no follow up. The interviewers talked about their people-oriented culture and values. It was clear they don't live up to these values since they couldn't be bothered to follow up. If this is the recruiting experience for leadership "executive" roles, I can imagine it's worse for others. They asked about my lack of experience in certain areas, which was likely why I was rejected. They didn't ask questions to check my readiness, and could have easily assessed my experience from my resume.

First, I had a quick chat with a recruiter about my background, SDR/BDR stuff I'd done, and what I was hoping for next. They also told me more about the company, the team, and what doing well there means. Then, I talked with the Inbound BDR Manager. It was more chill and we got into what I'd actually do day-to-day, how I find leads, deal with different types of leads, and manage my sales pipeline. The manager also asked some what-if questions to see how I'd figure things out and manage my time. After that, I got an email assignment to write a sample prospecting email based on a scenario. They wanted to see if I could make outreach personal, show I get the product, and get the value across fast. Next up was a practice call with someone on the team. I got info beforehand to prep like it was real. They checked my tone, how I structured the call, how I handled pushback, and if I could steer the conversation. The last interview was with the Head of BDR. It was a bigger picture chat about my career plans, why I'm driven, and if I fit the company vibe and future plans. It was also my time to ask about growing, how the team develops, and what they expect.

The interview process can be quick or drawn out depending on the candidate. I managed to get through the initial 3 stages in just 6 days, and then the final onsite was a full day with about 3 hours of interviews. First up was a recruiter call to gauge how strong of a candidate I was. It's important to explain your past projects clearly, even to someone non-technical. The more you can highlight the impact of your work, the better the recruiter will rate you. My recruiter said I was a 'Strong Candidate,' which I think really helped. Next was a skills assessment called CodeSignal, which could be done in Python or JavaScript; I used Python. It presented a real-world problem: build a Python class with specific methods, and you're given unit tests. You don't need a perfect score to advance; I reached the end of level 2 but ran out of time, assuming strong senior candidates would hit level 3. Then, I spoke with the Hiring Manager, who would be my manager if I got the job. This was similar to the recruiter call but more technical. Again, emphasize the IMPACT of your work. The recruiter mentioned I got a 'Strong Positive signal' here, which was a big plus. The final stage was a virtual onsite with two technical rounds and a conversation with my potential manager. They delve deeper into technical details, so be prepared to justify your design decisions.

The interview process included a recruiter screen, a hiring manager call, and panel interviews that covered a case study, SQL coding, and stakeholder interaction, followed by an offer. The recruiter was helpful and explained each interview stage and expectations clearly. The product analytics hiring team was also pleasant, and I generally felt comfortable during the interviews. However, the overall hiring experience was negative due to how the role was managed. I was initially assured that the salary range for the position had been increased and met my expectations. But after completing the interviews, they couldn't offer the same base salary that was previously discussed. I also found out the hiring manager had changed without me being informed, which made me feel the role might be more junior than presented and that I was being shopped around between teams. Additionally, speaking with team members suggested the role would focus more on reactive analytics using SQL rather than predictive modeling or AI, essentially making it a 'SQL monkey' position. A significant concern was the lack of diversity on the hiring team, which is important to me for career growth.