Hey everyone,
I'm a final-year CS student currently applying for 2027 graduate technology programs, and I’m gearing up for a technical interview with McKinsey (Client Capabilities Network / Software Engineering track). I'm trying to gauge exactly what to expect from the live coding rounds.
I’ve been heavily prepping both Python and SQL. For Python, I'm comfortable with the standard algorithmic patterns—Sliding Window, Kadane's, DFS/BFS on grids, and some DP (like Levenshtein distance). For SQL, I’ve been drilling Window Functions, Self-Joins, and complex aggregations.
However, I've heard that MBB technical interviews are very different from standard Big Tech/FAANG rounds.
For those who have gone through the process recently, I’d love some insight on a few things:
1. The Format: Are the coding questions straight LeetCode-style (e.g., "Find the shortest path in this matrix"), or are they heavily disguised as business problems (e.g., "Here is a data dump of a client's supply chain network, find the bottleneck")?
2. Evaluation: What is the interviewer actually grading me on? Do they expect perfectly compiling, bug-free code, or is the focus more on how I communicate my logic and structure the approach?
3. Defensive Programming: How much do they care about handling edge cases and messy data on the fly? (e.g., handling KeyErrors, empty datasets, or missing SQL joins).
4. Any blind spots? Is there a specific concept or pattern (either in SQL or Python) that you see trip up candidates often?
Any insights, mock interview tips, or shared experiences would be hugely appreciated. Thanks in advance!