First, I had an HR screening, followed by a Hiring Manager screening. Both were 30-minute interviews scheduled across two different weeks.
After that, I went through two technical interviews with Staff Software Engineers.
The first technical interview was based on a simple real-world use case from the company. What I found surprising is that I had explicitly been advised to prepare data structures and algorithms, including more advanced topics. As a result, I spent a significant amount of time reviewing concepts such as TreeMap, LinkedHashMap, ordering guarantees, and other non-trivial data structure implementations. In reality, the exercise consisted of using a simple HashMap, completing a straightforward method, and identifying a bug related to ordering. There was a clear mismatch between the preparation guidance and the actual interview content.
The second technical interview was even more disappointing. I was specifically told to prepare for topics such as large-scale ETL processes, high-throughput data systems, Kafka, distributed systems, scalability, and architecture challenges typically expected at a senior or staff engineering level.
Instead, the entire interview consisted of designing a simple data model for a peer-to-peer payments use case. There were no discussions around distributed systems, event-driven architectures, throughput, fault tolerance, consistency, scalability, data pipelines, or any of the topics I had been instructed to prepare for.
What I find most frustrating is not the difficulty of the interview itself, but the complete disconnect between the preparation guidance and the actual evaluation. I invested a considerable amount of time preparing for complex distributed systems topics because that is what I was explicitly told would be assessed. If the interview is ultimately focused on basic domain modeling, then candidates should be informed accordingly.
It is difficult to understand the rationale behind asking candidates to spend hours preparing for ETL systems, Kafka, distributed architectures, and large-scale system design when none of those subjects are evaluated during the interview process.
