# SWE II
**Role:** Software Engineer · **Level:** L3
**Company:** [Google](https://scaleengineer.com/companies/google)
**Difficulty:** Medium
**Salary:** US$110000 - US$150000
**Experience:** 2 - 5
**Timeline:** ~21 days
This interview process is for a Software Engineer (SWE II, L3) position at Google. It is designed to assess a candidate's technical skills, problem-solving abilities, and cultural fit within Google's engineering environment.
Canonical: https://scaleengineer.com/interviews/google/l3-software-engineer
---
## Overall evaluation

- Technical Skills
- System Design
- Behavioral and Cultural Fit

## Questions asked

- Given an array of integers, find the contiguous subarray with the largest sum.
- Design a URL shortening service.
- Explain the difference between a process and a thread.
- Describe a situation where you had to deal with a difficult stakeholder.
- How would you implement a Least Recently Used (LRU) cache?
- What are the trade-offs between SQL and NoSQL databases?
- Tell me about a time you failed and what you learned from it.
- Design a system to count the number of unique visitors to a website in real-time.
- How do you approach testing your code?
- What are your strengths and weaknesses as a software engineer?

## Preparation tips

### lists

- Master fundamental data structures and algorithms.
- Practice coding problems on platforms like LeetCode, HackerRank, and AlgoExpert.
- Study system design principles and common architectural patterns.
- Review object-oriented design principles.
- Prepare for behavioral questions by reflecting on past experiences using the STAR method.
- Understand the technologies and domains relevant to the specific role.
- Research Google's engineering culture and values.

### studyPlan

- {"title":"Data Structures and Algorithms","longDescription":"Weeks 1-2: Focus on core data structures (arrays, linked lists, stacks, queues, trees, graphs, hash tables) and fundamental algorithms (sorting, searching, recursion, dynamic programming). Practice implementing these from scratch and analyzing their time and space complexity.","shortDescription":"Weeks 1-2: Data Structures & Algorithms Fundamentals. Cover arrays, lists, stacks, queues, trees, graphs, hash tables, sorting, searching, recursion, DP. Analyze complexity."}
- {"title":"Advanced Algorithms and System Design Concepts","longDescription":"Weeks 3-4: Dive into more advanced algorithms and problem-solving techniques. Practice medium to hard LeetCode problems. Begin exploring system design concepts, including scalability, availability, and common design patterns (e.g., load balancing, caching, databases).","shortDescription":"Weeks 3-4: Advanced Algorithms & System Design Intro. Practice LeetCode (medium/hard). Study scalability, availability, load balancing, caching, databases."}
- {"title":"System Design and Behavioral Preparation","longDescription":"Weeks 5-6: Deepen system design knowledge. Work through common system design interview questions. Focus on designing scalable and reliable systems. Prepare for behavioral questions by recalling specific examples of teamwork, problem-solving, and leadership using the STAR method.","shortDescription":"Weeks 5-6: System Design Practice & Behavioral Prep. Design scalable systems. Use STAR method for behavioral questions."}
- {"title":"Mock Interviews and Final Review","longDescription":"Week 7: Mock interviews. Practice with peers or use online platforms to simulate the interview environment. Get feedback on your technical explanations and problem-solving approach. Review any weak areas identified during practice.","shortDescription":"Week 7: Mock Interviews & Review. Simulate interviews, get feedback, and review weak areas."}

## Location differences

- {"location":"Mountain View, CA","differences":{"tips":["Familiarize yourself with Google Cloud Platform (GCP) services.","Understand common distributed systems patterns and challenges.","Be prepared to discuss your experience with large-scale data processing.","Practice explaining complex technical concepts clearly and concisely."],"interviewFocus":["Distributed Systems Design","Scalability and Performance","Cloud Computing","Problem-solving in large-scale environments"],"commonQuestions":["Discuss a challenging project you worked on in a distributed systems environment.","How would you design a system to handle real-time traffic data for a major city?","Explain the trade-offs between different caching strategies.","Describe your experience with cloud platforms like GCP or AWS.","How do you approach debugging complex issues in a production environment?"]}}
- {"location":"New York, NY","differences":{"tips":["Review common machine learning algorithms and their applications.","Understand best practices for designing user-centric systems.","Practice coding challenges that involve optimizing for performance and memory.","Be ready to discuss security vulnerabilities and mitigation strategies."],"interviewFocus":["Machine Learning Applications","System Design with a focus on user experience","Code Optimization","Microservices Architecture","Web Security"],"commonQuestions":["How would you design a recommendation system for a streaming service?","Explain the principles of machine learning and how they apply to software engineering.","Describe a time you had to optimize code for memory usage.","What are the key considerations when designing a microservices architecture?","How do you ensure the security of a web application?"]}}

## Round 1: Data Structures and Algorithms
**Type:** Technical Interview (Coding) · **Difficulty:** Medium · **Duration:** 45 min
Coding challenge focusing on data structures and algorithms.
This round focuses on your core data structures and algorithms knowledge. You will be presented with one or two coding problems and expected to solve them on a shared editor. The interviewer will assess your problem-solving approach, coding skills, and ability to explain your solution and its complexity.
**Interviewers look for:** A systematic approach to problem-solving.; Proficiency in at least one programming language.; Ability to write clean, efficient, and correct code.; Clear communication of logic and trade-offs.; Understanding of time and space complexity.
**Evaluation criteria:** Correctness of the solution; Efficiency of the solution (time and space complexity); Clarity and organization of the code; Ability to communicate the thought process; Handling of edge cases
**Common rejection reasons:** Inability to solve coding problems within the given time.; Poor understanding of fundamental data structures and algorithms.; Code that is inefficient, buggy, or not well-structured.; Difficulty explaining thought process.; Lack of attention to edge cases.
## Questions

- Given a binary tree, invert the tree.
- Find the kth largest element in an unsorted array.

## Preparation tips

- Practice coding problems regularly.
- Focus on understanding the underlying data structures and algorithms.
- Be prepared to explain your thought process step-by-step.
- Consider edge cases and test your solution thoroughly.
- Write clean, readable, and well-commented code.

## Round 2: System Design
**Type:** Technical Interview (System Design) · **Difficulty:** Medium-Hard · **Duration:** 45 min
Design a scalable software system.
This round assesses your ability to design complex software systems. You'll be given an open-ended problem (e.g., design Twitter, design a URL shortener) and expected to propose a high-level design, discuss trade-offs, and justify your choices. This often involves distributed systems concepts.
**Interviewers look for:** A structured approach to system design.; Ability to break down complex problems.; Knowledge of common system design patterns and technologies.; Consideration of non-functional requirements (scalability, availability, latency).; Effective communication of design choices.
**Evaluation criteria:** Clarity and completeness of the design; Scalability and performance considerations; Robustness and fault tolerance; Understanding of trade-offs; Ability to justify design decisions
**Common rejection reasons:** Inability to design a scalable and robust system.; Lack of consideration for trade-offs and constraints.; Poor understanding of distributed systems concepts.; Failure to address potential failure points or bottlenecks.; Inability to communicate design choices effectively.
## Questions

- Design a system like Google Maps.
- Design a rate limiter.

## Preparation tips

- Study common system design interview questions and patterns.
- Understand concepts like load balancing, caching, databases (SQL vs. NoSQL), message queues, and APIs.
- Practice designing systems for scale and reliability.
- Be prepared to discuss trade-offs between different design choices.
- Clearly articulate your design and reasoning.

## Round 3: Behavioral and Team Fit
**Type:** Behavioral Interview · **Difficulty:** Medium · **Duration:** 45 min
Assesses teamwork, problem-solving, and cultural fit.
This round focuses on your behavioral and cultural fit. You'll be asked questions about your past experiences, how you handle specific situations (e.g., conflict resolution, dealing with ambiguity, project challenges), and your motivations. The STAR method (Situation, Task, Action, Result) is highly recommended for structuring your answers.
**Interviewers look for:** Examples of collaboration and teamwork.; How you handle challenges and failures.; Your ability to learn and adapt.; Your motivation and passion for technology.; Alignment with Google's principles (e.g., 'Focus on the user and all else will follow').
**Evaluation criteria:** Teamwork and collaboration skills; Problem-solving approach in past situations; Leadership potential; Adaptability and learning agility; Cultural fit with Google's values
**Common rejection reasons:** Lack of alignment with Google's values.; Poor communication or interpersonal skills.; Inability to provide specific examples of past experiences.; Negative attitude or lack of enthusiasm.; Dishonesty or inconsistency in responses.
## Questions

- Tell me about a time you had a conflict with a teammate and how you resolved it.
- Describe a challenging project you worked on and how you overcame obstacles.
- How do you stay updated with new technologies?

## Preparation tips

- Prepare specific examples from your past experiences using the STAR method.
- Reflect on Google's core values and how your experiences align with them.
- Be honest and authentic in your responses.
- Show enthusiasm and passion for the role and Google.
- Practice articulating your experiences clearly and concisely.