Round 1: Data Structures & Algorithms (DSA)

The questions were straightforward, like removing duplicates from a list and reversing a linked list. I felt okay about this round since the concepts were basic. However, I wasn’t 100% confident in my code efficiency and worried I might have made minor mistakes under timed conditions.

Round 2: Advanced SQL and Data Modeling

This was tougher than I anticipated. The question to find the third highest transaction per branch with ties had me thinking deeply about window functions. The schema design question required a detailed explanation of normalization, indexing, and partitioning strategies—something I’m experienced with but felt I could have structured better in my explanation. I walked out of this round a bit unsure if I fully showcased my expertise despite knowing the material.

Round 3: Data Engineering Concepts & ETL

I felt more in my zone here. Discussing the fraud detection pipeline and handling schema evolution was enjoyable because I’ve dealt with similar production challenges. Still, I noticed one question about monitoring pipelines caught me off guard slightly, and I fumbled a bit describing monitoring approaches in depth.

HR & Managerial Round:

This felt more like a friendly chat. Talking about career goals and cross-team collaboration was smooth, but I was slightly nervous discussing past production incidents honestly, worried it might reflect poorly.

Final Verdict:

I was selected for the role. The mix of strong technical skills, coupled with honest communication in HR, worked in my favor despite small doubts after some rounds.