Back-End Developer Interview Questions — NxtWave

nxtwave logo
nxtwave
Back-End DeveloperOngoing
September 1, 202536 reads

Summary

I recently interviewed for a Back-End Developer role at NxtWave, and this post details the specific questions I encountered across various domains, including Python, Django, Databases, and System Design.

Full Experience

I had a detailed interview experience for the Back-End Developer position at NxtWave. The interview process covered a wide range of topics, from basic personal background and team context questions to deep dives into Python algorithms, Django fundamentals, database design, and system design. There were also practical questions on production practices and API optimization. I've compiled all the exact questions I faced to help others prepare.

Interview Questions (25)

Q1
Tell Me About Yourself
Behavioral

Share a brief introduction about yourself, your background, and your relevant experience.

Q2
Describe Current Application and Problem Solved
Behavioral

Explain the application you are currently working on, the specific problem it addresses, and the target users it serves.

Q3
Jira Integration in Daily Workflow
Behavioral

Discuss how you integrate Jira into your team's daily development workflow.

Q4
Two Sum
Data Structures & AlgorithmsEasy

State the problem (Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.) and discuss possible approaches at a high level. No solution code.

Q5
Django Request/Response Lifecycle
Other

Explain the complete end-to-end lifecycle of a request and response in a Django application.

Q6
Authentication vs. Authorization in Django
Other

Define and contrast the concepts of authentication and authorization specifically within the context of Django.

Q7
Token-Based Authentication in Django
Other

Explain what token-based authentication is in Django and describe its appropriate use cases.

Q8
Lazy Loading in ORM
Other

Describe lazy loading in the context of databases or Object-Relational Mappers (ORMs). Explain situations where it is beneficial and where it can be detrimental.

Q9
Django Many-to-Many Relationship Modeling
Other

Explain how to model a many-to-many relationship between tables using Django's ORM.

Q10
Handling Long-Running Operations in Django
System Design

Describe strategies for executing heavy or long-running operations within a Django application to avoid blocking the main thread or requests.

Q11
Celery with Django
System Design

Explain what Celery is and discuss its common use cases when integrated with a Django application.

Q12
Django ORM Joins
Other

Explain the internal workings of Django ORM joins and demonstrate how to write them in a clean and efficient manner.

Q13
ACID Properties in Databases
Other

Explain the ACID properties (Atomicity, Consistency, Isolation, Durability) in the context of database transactions.

Q14
Atomicity in Transactional Systems
Other

Define atomicity and explain its significance in transactional database systems.

Q15
Database Indexing
Other

Explain what indexing is in a database and provide guidelines on when it is appropriate to add an index.

Q16
Internal Mechanism of Database Indexing
Other

Provide a high-level explanation of how database indexing works internally.

Q17
Indexing vs. GROUP BY
Other

Compare and contrast database indexing with the GROUP BY clause, highlighting their differences in purpose and how they affect query execution plans.

Q18
Minimal E-commerce Table Design
System Design

Design a table diagram for a minimal e-commerce application. Identify the core entities, their primary/foreign keys, and the relationships between them.

Q19
E-commerce Entity Relationships
System Design

Building on the minimal e-commerce design, identify and specify the types of relationships (one-to-one, one-to-many, many-to-many) that exist between the entities, indicating where each relationship applies.

Q20
End-to-End Production Web App Deployment
System Design

Explain the complete end-to-end deployment process for a production web application. Detail the necessary machines and services, including considerations for EC2, S3, databases, load balancers, networking, and observability tools.

Q21
Improving API Latency Under Load
System Design

Discuss strategies to improve API latency for a real service operating under heavy load, considering optimizations across the entire stack: network, application code, database, caching mechanisms, and deployment strategies.

Q22
Jira Integration with Development and Release Pipeline
Other

Explain how you integrate Jira into your development and release pipeline, referencing issue states, branching strategies, pull request (PR) reviews, and release notes.

Q23
Caching Strategies in Django/FastAPI
System Design

Identify optimal locations to implement caching within a Django or FastAPI service and specify the types of data or responses that would be suitable for caching.

Q24
Synchronous vs. Asynchronous Execution in Web API
System Design

Discuss the criteria and considerations for choosing between synchronous and asynchronous execution paths when designing a web API.

Q25
Monitoring Metrics and Logs for Latency/Error Budgets
System Design

Describe the key metrics and logs you would monitor to ensure compliance with latency and error budgets in a production system.

Discussion (0)

Share your thoughts and ask questions

Join the Discussion

Sign in with Google to share your thoughts and ask questions

No comments yet

Be the first to share your thoughts and start the discussion!