Amazon Online Assessment 2025: Questions Breakdown and Prep Guide

Thinking about interviewing at Amazon in 2025? You’ve probably heard about the infamous Amazon Online Assessment (OA). It’s a critical step in landing your dream role, but it doesn’t have to feel like a mystery. Whether you’re aiming for a software engineering, data, or operations role, this guide breaks down exactly what to expect, how to prepare, and which questions appear most frequently.

When to Expect the OA for Your Role

Not every Amazon candidate takes the OA. Typically, the OA is curated and systematically applied to candidates for technical and leadership-adjacent roles. Heads of engineering, VPs, and senior hiring managers collaborate to ensure that assessments align with the responsibilities of the role.

Expect the OA if you are applying for:

• Entry-level software engineering roles (SDE I/II) – Coding efficiency, data structures, and algorithms are tested.
• Data scientist or analytics positions – SQL, Python, and logic-based problem-solving are emphasized.
• Operations leadership programs – Quantitative reasoning, data interpretation, and logic puzzles are common.
• Any technical role requiring problem-solving under pressure – The OA ensures that only candidates who can think clearly under time constraints move forward.

Some candidates may request the OA to be waived, especially internal candidates or those with extensive relevant experience. However, even if waived, being prepared as if you’ll take the OA is your best strategy.

Pro tip: Treat the OA as the first “filter” in Amazon’s hiring process. Passing it demonstrates both technical skill and your ability to work under time pressure—something leaders care deeply about.

Roles That Commonly Require an OA at Amazon

Certain roles almost always include an OA as part of the process. Understanding which ones helps you prioritize preparation:

• Software Development Engineer (SDE) I & II – The OA typically includes coding challenges on arrays, strings, trees, and dynamic programming.
• Data Scientists / Data Analysts – Expect a combination of SQL, Python, and applied math problems.
• Applied Scientists / Machine Learning Engineers – Algorithmic and coding assessments dominate, sometimes with ML logic problems.
• Operations/Technical Program Managers – Quantitative reasoning, analytical puzzles, and logic tests are used to evaluate decision-making and problem-solving skills.

Amazon applies the OA consistently to ensure a standardized benchmark across teams, so understanding the role-specific patterns gives you an edge.

How to Prepare and Pass Amazon’s OA

Passing the Amazon OA isn’t about last-minute cramming—it’s about systematic preparation. Here’s how candidates consistently succeed:

1. Master Core Concepts – Focus on data structures (arrays, linked lists, trees, graphs), algorithms (sorting, searching, dynamic programming), and complexity analysis.
2. Practice Under Timed Conditions – The OA is timed. Simulate this by setting a 90–120 minute window for 5–6 questions. This builds speed and stress management.
3. Leverage Mock Assessments – Platforms like HackerRank, LeetCode, and Amazon-specific OA prep sites provide near-realistic simulations.
4. Review Previous OA Patterns – Amazon updates OAs every year, but fundamental problem types persist. Focus on arrays, strings, trees, graphs, DP, and basic SQL queries.
5. Strategically Analyze Questions – Break problems into smaller steps, write pseudocode, and check edge cases before coding.

Pro tip: Track both timing and correctness. Amazon is not only looking for the right answer—they care about your reasoning and efficiency. Practice “thinking out loud” as you solve problems—it mirrors what they expect in interviews.

Compiled List of Amazon OA Questions (2025 Version)

Here’s a sample list of questions based on recent HackerRank and LeetCode patterns:

1. Two Sum / Pair Sum Variations – Type: Array / Hashmap / Problem Solving
2. Longest Substring Without Repeating Characters – Type: String / Sliding Window / Problem Solving
3. Merge Intervals – Type: Array / Sorting / Interval Logic
4. Binary Tree Maximum Depth – Type: Tree / DFS / Recursion
5. Coin Change / Minimum Coins – Type: Dynamic Programming / Problem Solving
6. Linked List Cycle Detection – Type: Linked List / Two-Pointer Technique
7. Top K Frequent Elements – Type: Array / Hashmap / Heap / Priority Queue
8. Sliding Window Maximum – Type: Array / Sliding Window / Deque Optimization
9. Graph BFS/DFS Traversal – Type: Graph / BFS / DFS / Problem Solving
10. Product of Array Except Self – Type: Array / Prefix-Suffix Technique / Problem Solving
11. Valid Parentheses / Bracket Matching – Type: Stack / String / Problem Solving
12. Find Minimum in Rotated Sorted Array – Type: Array / Binary Search / Problem Solving
13. Dynamic Programming – Climbing Stairs – Type: Dynamic Programming / Recursion / Problem Solving
14. String Compression / Run-Length Encoding – Type: String / Two-Pointer / In-place Modification

This list is not exhaustive but highlights the types of questions Amazon loves.

1. Two Sum Variation

Type: Array / Hashmap / Problem Solving

Prompt (Variant): Given an array of integers and a target sum, find all unique pairs of indices where the numbers add up to the target. Return indices or values depending on the variant.

Trick: Use a hashmap to store seen values for O(n) lookup instead of brute-force O(n²). Watch for duplicates and ensure each pair is counted only once.

What it tests: Ability to manipulate arrays efficiently, understanding of hashmaps, and optimizing time complexity.

LeetCode cousin: Two Sum (#1)

2. Longest Substring Without Repeating Characters

Type: String / Sliding Window / Problem Solving

Prompt (Variant): Given a string, find the length of the longest substring without repeating characters.

Trick: Use a sliding window with a hashmap or array to track the last seen index of each character. Move the window dynamically instead of resetting on repeats.

What it tests: String manipulation, sliding window technique, ability to track state efficiently.

LeetCode cousin: Longest Substring Without Repeating Characters (#3)

3. Merge Intervals

Type: Array / Sorting / Interval Logic

Prompt (Variant): Given a list of intervals, merge all overlapping intervals and return the resulting list.

Trick: Sort intervals by start time first. Then iterate through, merging current and previous intervals as needed. Edge cases: fully nested intervals or single-element intervals.

What it tests: Sorting, interval reasoning, handling edge cases in array traversal.

LeetCode cousin: Merge Intervals (#56)

4. Binary Tree Depth

Type: Tree / DFS / Recursion

Prompt (Variant): Given the root of a binary tree, determine its maximum depth. Depth is the number of nodes along the longest path from root to leaf.

Trick: Recursive DFS is simplest. Edge cases: empty tree (return 0). Can also solve iteratively with BFS.

What it tests: Tree traversal, recursion, handling null nodes, and problem decomposition.

LeetCode cousin: Maximum Depth of Binary Tree (#104)

5. Coin Change

Type: Dynamic Programming / Problem Solving

Prompt (Variant): Given an array of coin denominations and a target amount, return the minimum number of coins required to make that amount. Return -1 if impossible.

Trick: Use DP array to store minimum coins for each amount up to target. Bottom-up iteration is more efficient than recursive memoization for large targets.

What it tests: Dynamic programming, iterative optimization, and problem decomposition.

LeetCode cousin: Coin Change (#322)

What Comes After the Online Assessment

Passing the OA is just the first step in Amazon’s multi-stage hiring process. While the OA filters candidates for technical competence and problem-solving under pressure, the next stages test your ability to apply that knowledge in real-world scenarios and demonstrate alignment with Amazon’s Leadership Principles. Here’s what comes next:

1. Technical Phone or Video Interview

Most candidates who pass the OA move to a technical phone or video interview. This stage usually lasts 45–60 minutes and focuses on:

• Coding and problem-solving: You’ll solve 1–2 algorithmic problems, similar to OA questions, but you’ll need to explain your thought process in real time.
• Data structures and complexity analysis: Interviewers expect you to discuss why you chose a specific approach and its efficiency.
• Behavioral alignment: Occasionally, Amazon interviewers may ask questions related to Leadership Principles even at this stage.

Pro tip: Practice “thinking out loud” during coding problems. Interviewers care as much about your reasoning and approach as they do about getting the right answer. Use platforms like LeetCode’s mock interview feature to simulate this experience.

2. Onsite Interview Loop

The onsite interview loop, often called the bar-raiser loop, is Amazon’s signature hiring stage. It usually includes 4–6 back-to-back interviews lasting 45–60 minutes each. Here’s what to expect:

• Coding and algorithm questions: Expect medium to hard-level coding questions that test problem-solving under time pressure.
• System design (for senior roles): You may be asked to design a scalable system or service, particularly for SDE II or higher.
• Behavioral interviews: Amazon heavily weighs its Leadership Principles. Candidates are asked to demonstrate past experiences showing customer obsession, ownership, bias for action, and more.
• Bar-raiser interview: One interviewer is designated as the “bar-raiser” whose primary job is to ensure that only candidates exceeding the standard move forward. They assess both technical skill and cultural fit.

Pro tip: Prepare STAR-format stories (Situation, Task, Action, Result) for behavioral questions. Have 5–6 examples ready that highlight leadership, problem-solving, and collaboration.

3. Post-Loop Feedback and Offer

After the onsite interviews:

• Interviewers submit evaluations – Each interviewer rates your performance on technical and behavioral competencies.
• Bar-raiser reviews – The bar-raiser ensures that the candidate meets or exceeds Amazon’s high hiring standards.
• Hiring committee decision – The final decision is made collectively, factoring in OA performance, interview loop feedback, and alignment with Leadership Principles.

If all goes well, you’ll receive an offer. Amazon offers are often tiered based on experience and performance, and may include base salary, stock options, and signing bonuses.

Pro tip: Use the offer stage to clarify role expectations, growth opportunities, and level placement. Your OA performance can sometimes impact your initial level if you performed exceptionally well.

4. Common Timeline

From passing the OA to receiving an offer, candidates typically experience a timeline like this:

• 1–2 weeks – Feedback and scheduling for technical phone/video interviews.
• 2–3 weeks – Onsite or virtual loop interviews.
• 1 week – Hiring committee review and offer decision.

Pro tip: Keep communication professional but proactive. Respond quickly to recruiter emails, confirm interview schedules, and ask clarifying questions when needed.

Key Takeaways

1. Passing the OA is just the start—Amazon evaluates both technical skill and leadership fit in the subsequent stages.
2. Bar-raisers are tough but fair; they exist to maintain high hiring standards.
3. Behavioral and coding preparation should be done in parallel, not sequentially.
4. The process is fast-paced but structured; knowing what to expect reduces anxiety and boosts performance.

Think of the OA as your gateway to the loop. Master it, and you’re well on your way to proving both your technical abilities and your potential as a future Amazon employee.

Conclusion

Amazon’s Online Assessment isn’t a random hurdle—it’s a curated, systematic tool used by leaders to identify top talent. Preparing with focus, practicing the right problem types, and understanding Amazon’s approach gives you a major edge.

Think of the OA as your first chance to showcase problem-solving under pressure. The better prepared you are, the smoother the rest of the process becomes. Start early, practice strategically, and turn the OA into your competitive advantage in landing a role at one of the world’s most data-driven companies.

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