Sr Java Developer Interview Questions

5,296 sr java developer interview questions shared by candidates

¿Que es lo más dificil que te ha tocado como desafio profesional? ¿Que te gusta hacer en tu tiempo libre? Todo lo referente a partrones de diseño, arquitectura, todo sobre POO, todo muy bien definido y detallado sobre java spring, cada función que se utilice se debe saber (fueron muy exagerados). Parte entrevista en ingles, conversación normal. SOLID.
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Senior Java Developer

Interviewed at Globant

3.6
Nov 6, 2022

¿Que es lo más dificil que te ha tocado como desafio profesional? ¿Que te gusta hacer en tu tiempo libre? Todo lo referente a partrones de diseño, arquitectura, todo sobre POO, todo muy bien definido y detallado sobre java spring, cada función que se utilice se debe saber (fueron muy exagerados). Parte entrevista en ingles, conversación normal. SOLID.

Code: Q1. Design and implement a distributed cache system in Java, capable of handling high-throughput read and write requests across multiple nodes. The goal is to ensure data consistency and fault tolerance in case of node failures. Implement the following features: 1. Data Partitioning: Use consistent hashing to distribute data across multiple cache nodes. 2. Fault Tolerance: When a node fails, ensure that its data is redistributed to other nodes without losing information. 3. Read and Write Operations: Provide efficient APIs for put(key, value) and get(key) operations. 4. Concurrency: Ensure thread-safe operations for the cache. 5. Scalability: Allow dynamic addition and removal of nodes without affecting system performance. Constraints: • Implement the solution in a single Java class for simplicity. • Do not use third-party libraries for consistent hashing. Deliverables: • A working Java implementation of the distributed cache. • Explanation of your design decisions, including trade-offs.
avatar

Senior Java Developer

Interviewed at Andersen Lab

4.4
Mar 14, 2025

Code: Q1. Design and implement a distributed cache system in Java, capable of handling high-throughput read and write requests across multiple nodes. The goal is to ensure data consistency and fault tolerance in case of node failures. Implement the following features: 1. Data Partitioning: Use consistent hashing to distribute data across multiple cache nodes. 2. Fault Tolerance: When a node fails, ensure that its data is redistributed to other nodes without losing information. 3. Read and Write Operations: Provide efficient APIs for put(key, value) and get(key) operations. 4. Concurrency: Ensure thread-safe operations for the cache. 5. Scalability: Allow dynamic addition and removal of nodes without affecting system performance. Constraints: • Implement the solution in a single Java class for simplicity. • Do not use third-party libraries for consistent hashing. Deliverables: • A working Java implementation of the distributed cache. • Explanation of your design decisions, including trade-offs.

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