Scale Engineer

Software Engineer

Software EngineerL3Medium

Asana's Software Engineer L3 interview process is designed to assess a candidate's technical proficiency, problem-solving abilities, and cultural fit within the company. The process typically involves multiple rounds, including technical interviews focusing on data structures, algorithms, and system design, as well as behavioral interviews to understand collaboration and communication skills.

Rounds·3

Timeline·~7d

Experience·1 - 3 yrs

Comp band·US$100000 - US$130000

Interview time·150 min

Evaluation

What they measure.

  • Problem-solving skills
  • Algorithmic knowledge
  • Data structure proficiency
  • System design capabilities
  • Coding proficiency and best practices
  • Communication skills
  • Teamwork and collaboration
  • Adaptability and learning agility
  • Cultural alignment with Asana's values

Preparation

How to prepare.

Tips

  1. Review fundamental data structures (arrays, linked lists, trees, graphs, hash maps) and algorithms (sorting, searching, dynamic programming, graph traversal).
  2. Practice coding problems on platforms like LeetCode, HackerRank, or Coderbyte, focusing on medium-difficulty problems.
  3. Understand common system design concepts such as scalability, availability, reliability, and trade-offs.
  4. Prepare to discuss your past projects in detail, focusing on your contributions, challenges, and learnings.
  5. Research Asana's products, mission, and values to understand how your skills and experience align.
  6. Practice answering behavioral questions using the STAR method (Situation, Task, Action, Result).
  7. Prepare questions to ask the interviewer about the role, team, and company culture.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Data Structures and Algorithms Fundamentals

Weeks 1-2: Data Structures & Basic Algorithms. Implement and analyze common DS. Practice sorting and searching.

Weeks 1-2: Focus on core data structures (arrays, linked lists, stacks, queues, trees, graphs, hash tables) and their common operations. Practice implementing them and analyzing their time and space complexity. Cover basic algorithms like sorting (quicksort, mergesort) and searching (binary search).

Questions

Commonly asked.

  • Given an array of integers, find the contiguous subarray with the largest sum.
  • Design a system to count the number of unique visitors to a website.
  • Explain the concept of recursion and provide an example.
  • How would you optimize a slow database query?
  • Tell me about a time you had to deal with ambiguity in a project.
  • What are your strengths and weaknesses?
  • Describe a situation where you had to influence a decision.
  • How do you stay updated with new technologies?

Locations

Regional differences.

Fig · Regions — 02 locations

01 / 02

Location

San Francisco

Interview focus

System Design (especially for distributed systems)Problem-solving and algorithmic thinkingCommunication and collaboration skills

Common questions

  • How would you design a URL shortener?
  • Explain the difference between a process and a thread.
  • Describe a challenging technical problem you solved.
  • Tell me about a time you disagreed with a teammate.

Tips

  • For San Francisco: Emphasize experience with scalable systems and cloud technologies (AWS, GCP).
  • For New York: Highlight experience with fast-paced environments and agile methodologies.
  • For international offices: Be prepared to discuss cultural nuances and global collaboration.

Rounds

Round-by-round.

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

Med

Technical Interview (Coding) · 45 min · Software Engineer

This round focuses on your ability to solve coding problems using data structures and algorithms. You will be asked to write code on a whiteboard or a shared editor to solve a specific problem. The interviewer will assess your problem-solving approach, your understanding of data structures and algorithms, and your coding style.

What they look for

A systematic approach to problem-solving.Ability to break down complex problems.Proficiency in writing clean, efficient code.Understanding of time and space complexity.

Evaluation

  • Correctness of the solution
  • Efficiency of the solution (time and space complexity)
  • Code clarity and readability
  • Problem-solving approach

Sample questions

  • Given a binary tree, invert the tree.

    Data StructuresAlgorithmsTreesRecursion

  • Find the kth smallest element in a sorted matrix.

    Data StructuresAlgorithmsArraysBinary Search

Prep for this round

  1. 01Practice coding on a whiteboard or in a plain text editor.
  2. 02Think out loud and explain your thought process.
  3. 03Consider edge cases and test your solution.
  4. 04Be prepared to discuss time and space complexity.

Common rejection reasons

  • ×Inability to articulate thought process clearly.
  • ×Lack of understanding of fundamental data structures and algorithms.
  • ×Poor coding practices or syntax errors.
  • ×Inability to solve the given problem within the time limit.

DSA

Coding questions at Asana.

Frequently reported on Asana loops

View all at Asana

Other guides

More at Asana.