Back End Engineer
Back End Engineer Interview Questions and Answers
Q1. Do you have experience with SQL and concurrency
Yes, I have experience with SQL and concurrency.
I have worked with SQL databases such as MySQL, PostgreSQL, and SQLite.
I am familiar with writing complex SQL queries to retrieve and manipulate data.
I have experience optimizing SQL queries for performance.
I have implemented concurrency control mechanisms like transactions and locking in SQL databases.
I have used tools like pgAdmin and MySQL Workbench for database management.
Q2. System design of token generation/verification service
Design a system for token generation and verification service
Use a secure algorithm to generate unique tokens
Implement a token storage system to store generated tokens
Include a verification mechanism to validate tokens
Consider scalability and performance for high volume token requests
Back End Engineer Interview Questions and Answers for Freshers
Q3. Describe architecture of the system you worked on
The system I worked on had a microservices architecture with Docker containers and Kubernetes for orchestration.
Microservices architecture
Docker containers for deployment
Kubernetes for orchestration
Q4. Describe your experience with NodeJS
I have extensive experience with NodeJS, including building RESTful APIs, real-time applications, and server-side rendering.
Built RESTful APIs using Express framework
Developed real-time applications with Socket.IO
Implemented server-side rendering with frameworks like Next.js
Used NodeJS for handling asynchronous operations efficiently
Q5. High level system design.
High level system design involves creating an overview of the system architecture and components.
Identify the main components and their interactions
Consider scalability, reliability, and performance
Choose appropriate technologies and frameworks
Ensure security and data privacy
Document the design and communicate it to stakeholders
Q6. Implement kafka like queue
Implementing a Kafka-like queue involves creating a distributed messaging system for handling large volumes of data.
Use Apache Kafka or another messaging system as a base for understanding the architecture.
Design a system with topics, partitions, producers, and consumers.
Implement fault tolerance and scalability features like replication and partitioning.
Ensure high throughput and low latency for message processing.
Consider implementing features like message retention, acknow...read more
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Q7. Design a simple LRU cache
LRU cache is a data structure that stores a fixed number of items and removes the least recently used item when full.
Use a doubly linked list to keep track of the order of items based on their usage.
Use a hashmap to quickly access items in the cache.
When an item is accessed, move it to the front of the linked list to mark it as the most recently used.
When adding a new item, check if the cache is full and remove the least recently used item from the end of the linked list.
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