Scale Engineer

Software Engineer

Software EngineerSoftware Engineer 2Medium to Hard

The interview process for a Software Engineer at Okta, level 2, is designed to assess technical proficiency, problem-solving skills, and cultural fit. It typically involves multiple rounds, including technical interviews, a system design interview, and a behavioral interview.

Rounds·3

Timeline·~14d

Experience·2 - 5 yrs

Comp band·US$110000 - US$150000

Interview time·150 min

Evaluation

What they measure.

  • Technical Skills: Proficiency in programming languages, data structures, algorithms, and system design.
  • Problem-Solving: Ability to analyze problems, devise solutions, and articulate them clearly.
  • Communication: Clarity in explaining technical concepts and thought processes.
  • Collaboration: Ability to work effectively with others and contribute to team goals.
  • Cultural Fit: Alignment with Okta's values and work environment.

Preparation

How to prepare.

Tips

  1. Review fundamental computer science concepts: data structures, algorithms, operating systems, databases.
  2. Practice coding problems regularly, focusing on different types of problems (arrays, strings, trees, graphs, dynamic programming).
  3. Study system design principles and common patterns (e.g., load balancing, caching, databases, message queues).
  4. Prepare for behavioral questions by reflecting on your past experiences using the STAR method (Situation, Task, Action, Result).
  5. Research Okta's products, services, and company culture.
  6. Understand the role of identity and access management in modern technology.
  7. Prepare questions to ask the interviewer about the role, team, and company.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Data Structures and Algorithms

Weeks 1-2: DSA fundamentals and practice.

Weeks 1-2: Focus on Data Structures and Algorithms. Cover arrays, linked lists, stacks, queues, trees (binary, BST, AVL), graphs, hash tables, heaps. Practice problems related to searching, sorting, recursion, and dynamic programming. Aim for 2-3 hours of study and practice daily.

Questions

Commonly asked.

  • Given an array of integers, find the contiguous subarray with the largest sum.
  • Design a system to handle real-time analytics for a website.
  • Tell me about a time you had to mentor a junior engineer.
  • How would you design a rate limiter?
  • Explain the concept of eventual consistency.
  • Describe your experience with cloud computing platforms.
  • What are the advantages of using microservices?
  • How do you approach debugging a complex issue?
  • Tell me about a project you are particularly proud of.
  • What are your strengths and weaknesses?

Locations

Regional differences.

Fig · Regions — 03 locations

01 / 03

Location

San Francisco Bay Area

Interview focus

Emphasis on practical application of data structures and algorithms.Understanding of distributed systems and scalability.Ability to write clean, efficient, and maintainable code.Problem-solving approach and communication skills.

Common questions

  • How would you design a URL shortener?
  • Explain the difference between SQL and NoSQL databases.
  • Describe a challenging technical problem you solved.
  • How do you handle concurrency in your applications?

Tips

  • Be prepared to whiteboard solutions.
  • Practice coding problems on platforms like LeetCode or HackerRank.
  • Familiarize yourself with common system design patterns.
  • Research Okta's products and technologies.

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 fundamental programming skills. You will be asked to solve one or two coding problems, typically involving data structures and algorithms. The interviewer will assess your ability to write clean, efficient, and correct code, as well as your problem-solving approach and communication skills. Be prepared to explain your thought process and discuss the time and space complexity of your solution.

What they look for

Ability to translate a problem into code.Understanding of time and space complexity.Clean and organized coding style.Ability to articulate the solution and trade-offs.

Evaluation

  • Correctness of the solution.
  • Efficiency of the algorithm (time and space complexity).
  • Code quality (readability, maintainability, style).
  • Problem-solving approach and communication.

Sample questions

  • Given a binary tree, find its maximum depth.

    TreeRecursionDepth First Search

  • Implement a function to reverse a linked list.

    Linked ListPointers

  • Find the kth smallest element in an unsorted array.

    ArraySortingQuickselect

Prep for this round

  1. 01Practice coding problems on platforms like LeetCode, HackerRank, or AlgoExpert.
  2. 02Review common data structures (arrays, linked lists, trees, graphs, hash maps) and algorithms (sorting, searching, recursion, dynamic programming).
  3. 03Practice explaining your solutions out loud.
  4. 04Be comfortable with at least one programming language (e.g., Python, Java, C++, Go).

Common rejection reasons

  • ×Inability to solve basic coding problems.
  • ×Poor understanding of fundamental data structures and algorithms.
  • ×Difficulty in explaining thought process.
  • ×Lack of attention to detail in code.

DSA

Coding questions at Okta.

Frequently reported on Okta loops

View all at Okta

Other guides

More at Okta.