Top 40+ Entry Level Software Engineer Interview Questions (2025)

The Entry Level Software Engineer Interview Process

Phone/Video Screening

Initial 30-minute conversation with a recruiter or engineer. Expect behavioural questions about your background, motivation, and key projects. This round assesses communication and cultural fit.

Technical Phone Screen

45-60 minute session involving 1-2 coding problems of easy-to-medium difficulty. You'll code in a shared editor (LeetCode, HackerRank, or similar). Focus on clear thinking and explaining your approach, not perfect solutions.

Onsite or Virtual Technical Interview

Usually 2-4 rounds (45-60 minutes each). Rounds typically cover coding/data structures, system design fundamentals, and sometimes a behavioural round. You may be asked to write code on a whiteboard or in an IDE.

System Design or Take-Home Project

Some companies ask entry level candidates to design a simple system or complete a small coding project. This tests architectural thinking and your ability to build features end-to-end.

Behavioural Round

Final round often focuses on teamwork, conflict resolution, learning agility, and how you handle failure. Questions draw from your academic or personal projects rather than workplace experience.

Behavioural Interview Questions for Entry Level Engineers

Tell me about a project you built during your studies or on your own. What was the biggest challenge?
Context: This is a core entry level question. Choose a project that demonstrates problem-solving, collaboration (if applicable), and your ability to overcome a real technical hurdle.
Sample Answer Guidance: During my final-year project, I built a real-time chat application with Node.js and Socket.io. I initially implemented message storage directly in memory, which caused data loss on server restart. I researched PostgreSQL, designed a database schema, and integrated it into the application. This taught me the importance of data persistence and how databases work in production systems.
Describe a time you had to learn a new technology or programming language quickly. How did you approach it?
Context: Entry level engineers must demonstrate learning agility. Employers want to see how you self-teach and what resources you rely on.
Sample Answer Guidance: When I decided to build a React web app, I had no prior experience. I started with the official React documentation and tutorials, then built small components to reinforce concepts. After a week, I built a portfolio project combining React, Redux, and an API. I relied on Stack Overflow and GitHub examples to debug issues. This showed me the value of structured learning followed by hands-on practice.
Tell me about a time you received critical feedback on your code or work. How did you respond?
Context: This reveals humility, growth mindset, and ability to handle critique — essential for junior engineers in code reviews.
Sample Answer Guidance: During a university group project, my teammate pointed out that my function was inefficient and hard to read. Instead of becoming defensive, I asked her to explain her concerns. She showed me better variable naming and suggested refactoring. I rewrote it, and the code became much clearer. I realised that seeking feedback is how I improve as a programmer.
Describe a time you worked on a team project where there was a disagreement. How did you handle it?
Context: Teamwork is crucial. Show that you can communicate, compromise, and focus on the goal rather than being right.
Sample Answer Guidance: In a hackathon, my team disagreed on the tech stack. One person wanted Django, I advocated for Express.js. Rather than argue, I suggested we spike both for 30 minutes to see which felt better. We chose Express because it was faster to prototype. This taught me that team velocity matters more than individual preferences.
What's a mistake you made in a coding project, and how did you recover from it?
Context: Shows self-awareness, problem-solving, and resilience. Everyone makes mistakes — how you respond matters.
Sample Answer Guidance: I spent two days building a feature only to realise I'd misunderstood the requirements. Instead of scrapping the work, I reviewed the requirements with my partner, identified the misalignment, and refactored the code to fit the actual need. I learned to clarify requirements upfront and check in mid-project.
Why do you want to become a software engineer? What attracts you to this field?
Context: Assess motivation and genuine interest. Avoid generic answers; mention specific experiences or problems you want to solve.
Sample Answer Guidance: I've always enjoyed solving puzzles, and coding lets me do that at scale. During a bootcamp, I built a tool that helped local nonprofits track volunteers, and seeing the real impact hooked me. I love that software engineering combines creativity, logic, and the ability to make a tangible difference.
Describe your experience with version control (Git). Have you collaborated on a codebase with others using Git?
Context: Git is fundamental. Discuss branching, pull requests, merge conflicts, and collaboration.
Sample Answer Guidance: I use Git daily for all my projects. In a group university project, we each worked on feature branches and submitted pull requests. I learned to write clear commit messages and how to resolve merge conflicts. This experience showed me how critical version control is for team collaboration.

Data Structures & Algorithms Questions

Given an array of integers, write a function to find two numbers that add up to a target sum. What is the time complexity of your solution?
Context: Classic two-pointer or hash map problem. Tests understanding of trade-offs between time and space complexity.
What interviewers look for: A strong answer sounds like: 'I'd use a hash map because lookups are O(1), and the trade-off is that I'm using O(n) extra memory instead of being O(1) space but O(n²) time with nested loops.' A weak answer sounds like: 'I'd use a hash map because that's what I learned in class' or not discussing the time/space trade-off at all.
Sample Answer Guidance: I'd use a hash map approach. Iterate through the array, and for each number, check if (target - number) exists in the hash map. If yes, return both numbers. If no, add the current number to the map. Time complexity is O(n), space complexity is O(n). A brute force nested loop would be O(n²) but slower.
What is the difference between a linked list and an array? When would you use each?
Context: Fundamental data structure comparison. Show understanding of insertion, deletion, access, and memory implications.
Sample Answer Guidance: Arrays provide O(1) random access by index but are fixed size and costly to insert/delete (O(n)). Linked lists are dynamic, with O(1) insertion/deletion if you have the node pointer, but require O(n) to access an element by index. Use arrays for fast lookups; use linked lists when you frequently add/remove items or don't know the size upfront.
Implement a function to reverse a linked list. Walk me through your approach.
Context: Common interview problem. Tests pointer manipulation and understanding of linked list structure.
Sample Answer Guidance: I'll use an iterative approach with three pointers: prev (initially null), curr (head), and next (to store curr.next before reassigning). Iterate through the list, reversing links as I go: curr.next = prev. Move prev and curr forward. Time is O(n), space is O(1). I could also solve recursively, but iterative is cleaner for interviews.
What is a binary tree? How is it different from a binary search tree (BST)?
Context: Foundational structures. Explain properties and implications for search/insertion.
Sample Answer Guidance: A binary tree is a tree where each node has at most two children. A BST is a binary tree where the left child is smaller and the right child is larger than the parent. This ordering property allows BSTs to support O(log n) search and insertion (in a balanced tree), whereas a regular binary tree offers no such guarantee.
Write a function to find the maximum depth of a binary tree.
Context: Recursive problem. Tests understanding of tree traversal and recursion.
Sample Answer Guidance: I'll use recursion. Base case: if node is null, return 0. Recursive case: return 1 + max(maxDepth(left), maxDepth(right)). This explores both branches and returns the longest path from root to leaf. Time is O(n) because we visit every node once.
Explain Big-O notation. What is the difference between O(n) and O(n²)?
Context: Critical for discussing algorithm efficiency. Show understanding of scaling and why it matters.
Sample Answer Guidance: Big-O describes how algorithm performance scales as input size grows. O(n) means the runtime grows linearly with n (e.g., iterating through an array once). O(n²) means it grows quadratically (e.g., nested loops). For n=1,000, O(n) might take 1,000 operations while O(n²) takes 1,000,000. This matters enormously at scale.
Describe how a hash map (dictionary) works. Why is lookup typically O(1)?
Context: Hash maps are ubiquitous. Explain hashing, collisions, and trade-offs.
Sample Answer Guidance: A hash map uses a hash function to map keys to array indices. When you insert a key-value pair, the key is hashed to an index, and the value is stored there. Lookup is O(1) on average because you hash the key and directly access that index. Collisions (two keys hashing to the same index) are handled via chaining or open addressing, which can degrade performance if there are many collisions, hence 'average' O(1).
What sorting algorithms do you know? Explain the time complexity and use cases for merge sort vs. quicksort.
Context: Tests knowledge of common algorithms and trade-offs. Shows algorithmic thinking.
Sample Answer Guidance: Merge sort is O(n log n) in all cases, stable, but uses O(n) extra space. It's predictable and good for linked lists or when stability matters. Quicksort is O(n log n) average but O(n²) worst case, O(log n) space due to recursion, faster in practice for arrays. I'd use merge sort for guarantees, quicksort for typical performance.

How to Structure a Technical Answer When You Lack Experience

Clarify the Problem — Ask clarifying questions (constraints, input size, edge cases).

Discuss Your Approach — Walk through your logic step-by-step before coding. Use pseudocode if unsure of syntax.

Write Code Carefully — Focus on correctness over speed. Add comments.

Analyse Complexity — Discuss time and space complexity. If your solution isn't optimal, acknowledge it and suggest improvements.

Test and Edge Cases — Trace through your code with examples, especially edge cases (empty arrays, single element, etc.).

Learn from Mistakes — If you get stuck, voice your thought process. Interviewers value problem-solving over perfect answers.

OOP, Language Fundamentals & Code Quality Questions

Explain the four pillars of object-oriented programming: encapsulation, abstraction, inheritance, and polymorphism.
Context: Core OOP knowledge. Provide concise explanations with examples.
Sample Answer Guidance: Encapsulation hides internal data (private fields) and exposes a public interface. Abstraction simplifies complexity by showing only essential features. Inheritance allows classes to inherit properties and methods (code reuse). Polymorphism means objects of different classes can be used interchangeably (method overriding). For example, encapsulation: a BankAccount class hides the balance and offers deposit/withdraw methods. Polymorphism: a Shape class defines draw(); Circle and Square override it differently.
What is the difference between a class and an object?
Context: Foundational OOP terminology.
Sample Answer Guidance: A class is a blueprint or template that defines attributes and methods. An object is an instance of a class with specific values for those attributes. For example, 'Dog' is a class with attributes like name and breed; my specific dog 'Buddy' (a golden retriever) is an object.
Explain the difference between public, private, and protected access modifiers.
Context: Encapsulation concept. Show understanding of access control.
Sample Answer Guidance: Public members are accessible from anywhere. Private members are only accessible within the class itself. Protected members are accessible within the class and subclasses. Using private fields and public methods lets you control how data is accessed and modified, improving encapsulation and maintainability.
What is the DRY principle? Give an example of when you violated it and how you fixed it.
Context: Code quality and refactoring awareness. Look for self-reflection.
Sample Answer Guidance: DRY = Don't Repeat Yourself. Avoid duplicating logic across your codebase. I once wrote the same validation logic in three different functions. I realised I should extract it into a shared validate() function that all three call. This reduced bugs and made maintenance easier.
Explain SOLID principles and why they matter for code quality.
Context: Advanced code design. Tests understanding of design philosophy.
Sample Answer Guidance: SOLID is an acronym for five principles: Single Responsibility (one class, one job), Open-Closed (open for extension, closed for modification), Liskov Substitution (subclasses replaceable for base class), Interface Segregation (specific interfaces over general ones), and Dependency Inversion (depend on abstractions). Following SOLID makes code modular, testable, and maintainable. In a project, I separated validation into its own module rather than mixing it with business logic, following Single Responsibility.
How do you debug a piece of code? Walk me through your debugging process.
Context: Problem-solving approach and tools knowledge.
Sample Answer Guidance: I start by understanding what the code should do and what it actually does. I use print statements or a debugger (like Chrome DevTools or Python's pdb) to inspect variable values at different points. I isolate the problematic section, form a hypothesis, test it, and repeat. Version control and Git diff help me see what changed. I also check error messages and stack traces carefully.
What is a design pattern? Describe one pattern you've encountered or studied.
Context: Shows awareness of proven solutions. Entry level may not have used many, but should know a few conceptually.
Sample Answer Guidance: A design pattern is a reusable solution to a common problem in software design. The Model-View-Controller (MVC) pattern separates an application into three components: Model (data), View (UI), and Controller (logic). I've used MVC in a web project with Express (controller), EJS (view), and a database (model). This separation makes the code modular and testable.
How does version control (Git) improve code quality and collaboration?
Context: Best practices and tooling awareness.
Sample Answer Guidance: Git enables collaboration by letting multiple developers work on different branches simultaneously. It provides history, so you can revert bad changes. Code review via pull requests catches bugs and enforces standards before merging. Commit messages document why changes were made. This creates accountability and prevents accidental overwrites.

System Awareness & Problem-Solving Questions

How does a relational database differ from other types of databases? Why would you use a relational database like PostgreSQL?
Context: Fundamental data storage knowledge. Shows understanding of data structure and use cases.
Sample Answer Guidance: Relational databases (PostgreSQL, MySQL) organise data into tables with rows and columns, with relationships defined via foreign keys. They enforce schemas and provide ACID guarantees (reliability). Other types: NoSQL databases (MongoDB) are flexible but lack strict relationships. I'd use a relational database when my data has clear structure and relationships (users, posts, comments), like a social network.
What is an API? How does a REST API differ from other API styles?
Context: Web fundamentals. Understanding of how services communicate.
Sample Answer Guidance: An API (Application Programming Interface) allows one piece of software to request services from another. REST (Representational State Transfer) uses HTTP methods (GET, POST, PUT, DELETE) to manipulate resources identified by URLs. A GET /users/1 retrieves user 1. A POST /users creates a new user. REST is stateless and scales well. Other styles like GraphQL or SOAP exist but REST is most common for web services.
Explain the HTTP request-response cycle. What happens when you type a URL into your browser?
Context: Web fundamentals. Shows understanding of client-server communication.
Sample Answer Guidance: When I type a URL, the browser sends an HTTP GET request to the server. The server processes it, retrieves the resource, and responds with an HTTP status code (200 OK) and the requested resource (HTML, JSON, etc.). The browser parses the HTML, downloads CSS and JavaScript, renders the page, and executes scripts. The entire cycle involves DNS lookup, TCP connection, TLS handshake (for HTTPS), and the actual request-response.
What is a database index? Why would you add an index to a table column?
Context: Database optimisation basics. Shows awareness of performance considerations.
Sample Answer Guidance: An index is a data structure (like a B-tree) that speeds up lookups on a table column. Without an index, a query must scan the entire table (O(n)). With an index on that column, lookups are O(log n). Trade-off: indices consume extra memory and slow down writes (because the index must be updated). I'd index columns frequently used in WHERE clauses (e.g., user_id, email).
Describe a simple system you've built. How did the frontend and backend communicate? What storage did you use?
Context: Holistic system thinking. Tests whether you understand all layers of a web application.
Sample Answer Guidance: I built a to-do list app with a React frontend and Express backend. The frontend made HTTP requests (fetch API) to the backend endpoints (/todos, /todos/:id). The backend handled logic and queries a PostgreSQL database. When I added a to-do, React sent a POST request; the backend inserted it into the database and returned the created record; the frontend updated the UI. This taught me how frontend, backend, and database interact.
What is the difference between SQL and NoSQL databases? When would you choose each?
Context: Database trade-offs. Shows analytical thinking about technology choices.
Sample Answer Guidance: SQL (relational) databases use structured schemas and relationships (PostgreSQL, MySQL). NoSQL databases are flexible and unstructured (MongoDB, Firebase). SQL is great for consistent, related data (banking, e-commerce). NoSQL suits rapidly evolving schemas or massive scale with simpler queries. For my to-do app, I chose PostgreSQL because users, lists, and items have clear relationships.
How do you think about scalability when designing a system?
Context: Introduction to system design thinking for entry level. Keep it high-level.
Sample Answer Guidance: Scalability is the system's ability to handle growth (more users, more data). Early on, a monolithic architecture works fine. As users grow, I'd consider load balancing (distributing requests across multiple servers), caching (Redis for frequent queries), and database optimisation. Eventually, microservices might separate concerns. I think about which parts are bottlenecks and optimise those. It's about anticipating growth without over-engineering upfront.
What is a transaction in a database, and why do ACID properties matter?
Context: Data integrity and reliability fundamentals. Tests understanding of database guarantees.
Sample Answer Guidance: A transaction is a sequence of database operations that executes atomically—all succeed or all fail together. ACID properties ensure reliability: Atomicity (all or nothing), Consistency (valid state before and after), Isolation (concurrent transactions don't interfere), Durability (committed data persists). Without ACID, a bank transfer could debit one account but fail to credit another, leaving money lost. Relational databases like PostgreSQL enforce ACID; NoSQL databases often sacrifice some ACID guarantees for performance.
What is containerisation, and why is Docker useful?
Context: Modern deployment concepts. Entry level may not have used Docker, but should understand the concept.
Sample Answer Guidance: Containerisation packages an application and its dependencies into a container (Docker image) that runs consistently anywhere. Without containers, 'it works on my machine' is a common problem. Docker ensures dev, test, and production environments are identical. I've used Docker locally to match production setups. It simplifies deployment and collaboration across teams.

What Interviewers Look For in Entry Level Candidates

Problem-Solving Ability: Can you break down unfamiliar problems, ask clarifying questions, and reason through solutions? This matters more than perfect code.

Communication: Do you explain your thinking clearly? Can you articulate trade-offs and acknowledge limitations? Clear communication is crucial in teams.

CS Fundamentals: Do you understand data structures, algorithms, and complexity analysis? Fundamentals don't change; frameworks do.

Learning Agility: How quickly do you pick up new technologies? Do you take initiative to learn? Entry level roles value growth potential.

Collaboration & Teamwork: Can you work with others, accept feedback, and contribute to team goals? Discuss team projects and how you handled disagreements.

Attention to Detail: Do you test your code? Do you handle edge cases? Sloppy mistakes (off-by-one errors, ignoring null checks) signal carelessness.

Curiosity & Growth Mindset: Do you ask questions? Show interest in how things work? Demonstrate a desire to improve? Humility and eagerness matter for junior hires.

Frequently Asked Questions

What is the difference between an entry level and junior software engineer interview?

Entry level interviews target new graduates, bootcamp grads, or career changers with zero professional experience. They focus on computer science fundamentals, academic projects, and learning ability. Questions are about hackathons, coursework, and self-taught projects. Junior engineer interviews (0-2 years professional experience) are workplace-focused, asking about real production systems, code reviews, bug fixes, and collaboration in a team environment. If you have professional experience, review our junior software engineer interview guide.

How should I prepare for a coding interview if I'm nervous about live coding?

Practice is the best cure. Use platforms like LeetCode or HackerRank to solve problems daily. Start with easy problems, understand the approach, then code it out loud. Record yourself or practise with a friend. During the actual interview, remember that interviewers expect imperfection; they value your process. Speak through your thinking, ask clarifying questions, and don't panic if you make a mistake—debugging is part of real development.

Should I memorise sorting algorithms and data structure implementations?

Understand them deeply, but you don't need to memorise verbatim. You should know how merge sort and quicksort work, their complexity trade-offs, and when to use each. For linked list reversal or binary tree traversal, practise until you can code them comfortably, but if you forget a detail, it's okay to ask or think aloud. The key is understanding the logic, not memorisation.

How do I answer behavioural questions without workplace experience?

Use academic projects, hackathons, group coursework, or personal projects. Apply the STAR method: Situation (describe the project), Task (your role and challenge), Action (what you did), Result (outcome and learning). For example, 'During a hackathon, I built a feature but miscalculated the time. I prioritised core functionality and delivered a working MVP.' The interviewer wants to see how you handle challenges and learn, not production experience.

What if I don't know the answer to a technical question?

Don't panic or make up an answer. Be honest: 'I haven't worked with that specific technology, but I'd approach it by...' Then show your problem-solving logic. Ask clarifying questions. For algorithm problems, discuss brute force first, then optimise. Interviewers respect candidates who think out loud and admit unknowns; they disrespect candidates who pretend to know when they don't.

How important is having a portfolio or GitHub projects?

Very important. A portfolio demonstrates that you can build complete projects from idea to deployment. Include 2-3 projects (full stack app, interesting algorithm implementation, or open-source contribution). Your code should be readable, documented, and deployed. Interviewers often ask about your projects, so choose ones you can speak confidently about. A strong portfolio can sometimes offset weaker interview performance.

How can I improve my problem-solving speed for coding interviews?

Consistency beats intensity. Solve one problem daily, focusing on understanding the pattern, not speed. After solving, review optimal solutions to learn techniques. Identify recurring patterns (two pointers, sliding window, dynamic programming). Time yourself after weeks of practice. Speed comes naturally with familiarity, but accuracy and communication matter more than blazing through code.

What should I do after an interview to follow up?

Send a thank-you email within 24 hours to your interviewer(s), thanking them for their time and reiterating your interest. Mention a specific topic you discussed to personalise it. Keep it brief (3-4 sentences). If you made a mistake during the interview, you can briefly address it ('I realised later that a hash map would be more efficient than my nested loop approach'). Professionalism in follow-up leaves a positive impression.

Entry Level Software Engineer Interview Questions & Answers

The Entry Level Software Engineer Interview Process

Phone/Video Screening

Technical Phone Screen

Onsite or Virtual Technical Interview

System Design or Take-Home Project

Behavioural Round

Behavioural Interview Questions for Entry Level Engineers

Data Structures & Algorithms Questions

How to Structure a Technical Answer When You Lack Experience

OOP, Language Fundamentals & Code Quality Questions

System Awareness & Problem-Solving Questions

Practice with a Real Interview Simulation

What Interviewers Look For in Entry Level Candidates

Frequently Asked Questions

Stop Imagining—Start Interviewing

Entry Level Software Engineer Interview Questions & Answers

The Entry Level Software Engineer Interview Process

Phone/Video Screening

Technical Phone Screen

Onsite or Virtual Technical Interview

System Design or Take-Home Project

Behavioural Round

Behavioural Interview Questions for Entry Level Engineers

Data Structures & Algorithms Questions

How to Structure a Technical Answer When You Lack Experience

OOP, Language Fundamentals & Code Quality Questions

System Awareness & Problem-Solving Questions

Practice with a Real Interview Simulation

What Interviewers Look For in Entry Level Candidates

Frequently Asked Questions

Explore by Experience Level

Related Interview Guides

Stop Imagining—Start Interviewing