Software Engineer IV

Software EngineerL9Hard

The Software Engineer IV (L9) interview at Swiggy is a rigorous process designed to assess candidates for senior-level technical expertise, problem-solving abilities, and leadership potential. It typically involves multiple rounds focusing on data structures, algorithms, system design, and behavioral aspects, ensuring candidates can handle complex challenges and contribute significantly to Swiggy's engineering goals.

Rounds·4

Timeline·~7d

Experience·6 - 10 yrs

Comp band·US$35000 - US$45000

Interview time·225 min

Evaluation

What they measure.

  • Problem-solving skills
  • Algorithmic thinking
  • Data structures knowledge
  • System design capabilities
  • Scalability and performance considerations
  • Code quality and best practices
  • Communication skills
  • Behavioral and cultural fit
  • Leadership potential
  • Experience with relevant technologies

Preparation

How to prepare.

Tips

  1. Review fundamental data structures and algorithms.
  2. Practice coding problems on platforms like LeetCode, HackerRank, etc.
  3. Study system design principles and common patterns.
  4. Prepare for behavioral questions by reflecting on past experiences using the STAR method.
  5. Research Swiggy's products, services, and recent news.
  6. Understand the company's culture and values.
  7. Prepare questions to ask the interviewer.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Data Structures and Algorithms

Weeks 1-2: Data Structures & Algorithms fundamentals. Practice 5-7 problems/day.

Weeks 1-2: Focus on core data structures (Arrays, Linked Lists, Trees, Graphs, Hash Tables) and algorithms (Sorting, Searching, Dynamic Programming, Greedy Algorithms). Practice implementing these in your preferred language. Aim for at least 5-7 problems per day.

Questions

Commonly asked.

  • Design a URL shortener service.
  • How would you design a rate limiter?
  • Explain the CAP theorem and its implications.
  • Describe a time you had to deal with a production issue. What was your approach?
  • How do you mentor junior engineers?
  • What are your thoughts on technical debt?
  • Design a system to handle real-time notifications for Swiggy.
  • How would you optimize database queries for a large e-commerce platform?
  • Tell me about a challenging project you worked on and how you overcame obstacles.

Locations

Regional differences.

Fig · Regions — 02 locations

01 / 02

Location

Bangalore

Interview focus

System design for scalability and reliabilityDeep understanding of distributed systemsExperience with cloud-native technologies (AWS, GCP, Azure)Problem-solving in a high-pressure, fast-paced environmentLeadership and mentorship capabilities

Common questions

  • How would you design a real-time order tracking system for Swiggy?
  • Discuss the challenges of scaling a food delivery platform during peak hours.
  • Explain your experience with distributed systems and microservices architecture.
  • How do you handle concurrency issues in a high-throughput system?
  • Describe a complex technical problem you solved and the impact it had.

Tips

  • Emphasize experience with large-scale distributed systems.
  • Be prepared to discuss trade-offs in system design decisions.
  • Showcase leadership and ability to mentor junior engineers.
  • Understand Swiggy's business context and challenges.
  • Practice explaining complex technical concepts clearly and concisely.

Rounds

Round-by-round.

Expand a step for evaluation criteria, sample questions, and prep notes.

Hard

Data Structures And Algorithms Interview · 60 min · Senior Software Engineer

This round focuses on your fundamental computer science knowledge. You will be asked to solve 1-2 coding problems that require a good understanding of data structures and algorithms. The interviewer will assess your ability to analyze the problem, devise an efficient solution, write clean and correct code, and discuss the time and space complexity of your solution. Expect questions that test your problem-solving skills under pressure.

What they look for

Strong grasp of data structures and algorithmsAbility to translate problem statements into codeLogical thinking and analytical skillsAttention to detail

Evaluation

  • Correctness of the solution
  • Efficiency of the algorithm (time and space complexity)
  • Code clarity and readability
  • Ability to handle edge cases
  • Problem-solving approach

Sample questions

  • Given a binary tree, find the lowest common ancestor of two given nodes.

    Data StructuresTreesAlgorithms
  • Implement a function to find the k-th largest element in an unsorted array.

    ArraysAlgorithmsSorting
  • Design a data structure that supports insert, delete, search, and getRandom in O(1) time.

    Data StructuresHash TablesArrays

Prep for this round

  1. 01Practice coding problems regularly.
  2. 02Understand the trade-offs between different data structures and algorithms.
  3. 03Be able to explain your thought process clearly.
  4. 04Practice writing code on a whiteboard or shared editor.
  5. 05Focus on optimizing your solutions.

Common rejection reasons

  • ×Inability to articulate thought process clearly
  • ×Incorrect or inefficient algorithmic solutions
  • ×Poor coding practices
  • ×Lack of understanding of time and space complexity

DSA

Coding questions at Swiggy.

Frequently reported on Swiggy loops

Other guides

More at Swiggy.