Atlassian

Atlassian's engineering interview process is designed to evaluate a candidate's technical proficiency, problem-solving abilities, and alignment with the company's core values. The process typically includes multiple stages:

1. Resume Review: Focuses on relevant experience and technical skills.
2. Phone Screen: Discusses background, technical knowledge, and motivation for applying.
3. Technical Interviews: Evaluates coding skills, system design, and problem-solving through exercises and discussions.
4. Behavioral Interviews: Assesses cultural fit and alignment with Atlassian's values.
5. Final Interview: Involves a comprehensive discussion with the hiring manager and possibly a take-home assignment.

Throughout these stages, Atlassian emphasizes clear communication, collaboration, and a growth mindset. Candidates are encouraged to ask clarifying questions, articulate their thought processes, and demonstrate how they embody the company's values. (glassdoor.com)

Assessment Rubric Overview

The "Similar Numbers" problem assesses several key competencies:

1. Technical Competencies:

   • Algorithmic Thinking: Ability to design efficient algorithms for counting permutations and handling large numbers.
   • Data Structures: Proficiency in utilizing appropriate data structures to manage and compare digit frequencies.
   • Edge Case Handling: Skill in identifying and managing edge cases, such as leading zeros and large input sizes.

2. Behavioral Traits and Problem-Solving Approaches:

   • Analytical Thinking: Capacity to break down complex problems into manageable components.
   • Attention to Detail: Meticulousness in considering all aspects of the problem, including constraints and special cases.
   • Communication Skills: Effectiveness in articulating thought processes and solutions clearly.

3. Assessment Process Expectations:

   • Problem-Solving Discussion: Engagement in a dialogue to understand the candidate's approach to the problem.
   • Solution Evaluation: Assessment of the proposed solution's correctness, efficiency, and scalability.
   • Behavioral Interview: Exploration of past experiences to gauge alignment with Atlassian's values.

4. Preparation Recommendations:

   • Algorithm Practice: Regularly solve problems involving permutations, combinations, and number theory.
   • Data Structure Mastery: Deepen understanding of data structures like hash maps and arrays.
   • Edge Case Identification: Develop skills in recognizing and handling edge cases in problem scenarios.
   • Behavioral Reflection: Prepare to discuss past projects, challenges, and how they align with Atlassian's values.

5. Evaluation Criteria and Technical Concepts:

   • Algorithm Efficiency: Solutions should be optimized for time and space complexity.
   • Code Quality: Emphasis on clean, readable, and maintainable code.
   • Problem Understanding: Demonstrated comprehension of the problem requirements and constraints.
   • Cultural Fit: Alignment with Atlassian's values, including collaboration and continuous improvement.

By focusing on these areas, candidates can effectively prepare for the "Similar Numbers" problem and align their approach with Atlassian's interview expectations.