Top K Frequent Elements for Senior Backend Engineer — Interview Guide

• Count frequencies with a hash map in O(n).
• A min-heap of size k keeps the top k by frequency in O(n log k).
• Bucket sort by frequency achieves O(n) when values are bounded.

import heapq, collections
def top_k(nums, k):
    freq = collections.Counter(nums)
    return heapq.nlargest(k, freq.keys(), key=freq.get)

• Scalability reasoning — capacity estimates and bottlenecks.
• Trade-off articulation — SQL vs NoSQL, sync vs async, strong vs eventual.
• Data integrity — transactions, idempotency, reconciliation.
• Operational maturity — monitoring, failure modes, on-call thinking.