The interview process consisted of a single technical round conducted over video call.

The discussion focused mainly on Java fundamentals, JVM internals, data structures, Kafka, caching, and distributed system concepts.

There was no coding exercise; most questions were scenario-based and conceptual. The interviewer asked follow-up questions to evaluate real-world experience and depth of understanding.

Overall, the process was structured, technical, and focused on backend engineering skills rather than puzzles.

The interview mainly focused on Java internals, system design basics and distributed systems.

1. Retry mechanism – disadvantages. Explain problems with retries in distributed systems (duplicate requests, cascading failures, increased load, thundering herd, idempotency issues, etc.).
2. Design a cache system. High-level cache design – eviction strategy, TTL, consistency, read-through / write-through, local vs distributed cache, failure handling.
3. What is Jitter? Why jitter is added to retry / backoff strategies and how it helps avoid retry storms.
4. System.arraycopy(). How it works internally, performance benefits compared to manual copy, native implementation, and when to use it.
5. Types of Garbage Collection in Java. Different GC algorithms (Serial, Parallel, CMS, G1, ZGC / Shenandoah) and when each is suitable.
6. Java Stream API – handling Map. Operations on Map using streams – converting Map to stream, grouping, filtering, collecting to Map, handling duplicate keys in collectors.
7. Kafka acknowledgement configuration. Explanation of acks=0, acks=1, acks=all and trade-offs between performance and durability.
8. SQL – find second highest salary. Different approaches (subquery, DISTINCT, LIMIT/OFFSET, window functions like DENSE_RANK()).
9. HashMap internal working. How HashMap works internally (hashing, buckets, collision handling, treeification), HashMap vs ConcurrentHashMap, when and how HashMap resizes, and effect of initial capacity and load factor.