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How to Prepare for Amazon

Amazon filters on OA first, then loops DSA with Leadership Principles in every round. Bar Raiser is real. You need clean code under time and STAR stories with numbers - not buzzwords.

First round: Amazon OA (2 DSA + work simulation + LP MCQs)

Time split that matches how candidates report outcomes (not a marketing pie chart):

  • DSA 55%
  • System design / CS 20%
  • Behavioral 15%
  • Mocks 10%

Patterns are from student reports and vary by role and drive. Trust your college placement email over blog folklore.

Stage Time What they check
Online assessment 70-120 min 2 coding + simulation/debug + LP MCQs
Technical loops 45-60 min each DSA + LP probes in the same round
System design / depth varies by level SDE-1 light; SDE-2+ heavier
Bar Raiser 45-60 min Independent bar check - consistency matters
HR / offer 20-30 min Role, location, CTC
  • Master DSA (graphs, sliding window, bit manipulation, DP) - practice 150+ problems on LeetCode (Amazon tag)
  • Study system design basics (SDE-1) and scalable systems (SDE-2+)
  • Prepare STAR stories for all 16 Amazon Leadership Principles
  • Practice coding problems in Java/C++/Python
  1. One timed block that matches Amazon’s first round (OA coding)
  2. Log misses: topic + why you failed (speed, concept, carelessness)
  3. Re-solve yesterday’s misses cold
  4. Twice a week: 10 minutes of resume/project narration out loud
Week Focus Exit criteria
1-2 Arrays, hashing, two pointers, sliding window 40+ clean mediums
3-4 Trees, graphs, BFS/DFS, heaps Implement BFS/DFS cold
5-6 DP + timed 2-problem mocks Finish both with tests
7 System design lite + CS revision Explain a URL shortener / newsfeed at SDE-1 depth
8 Behavioral + weak-topic closure STAR bank ready; re-solve misses
  • Order problems by confidence after a 3-4 minute skim
  • Passing test cases beats a brilliant half-solution
  • Invent edge cases before submit; watch timeboxes
  • Restate → brute force → optimize → code → test
  • Speak complexity and trade-offs out loud.
  • Tie CS answers to a project when it strengthens the point
  • Why Amazon, why this team/role, location flexibility
  • STAR with a metric; pick 2-3 real company values and prepare proof
  • LeetCode Amazon-tag mediums: graphs, sliding window, heaps, DP
  • Timed 2-problem OA mocks until both pass with edge cases
  • STAR bank mapped to Customer Obsession, Ownership, Dive Deep, Deliver Results
  • Work-simulation style judgment: prioritize, write clear responses
  • One language you can debug live (Java/C++/Python)
  • Arrays, strings, hashing, trees, graphs
  • Complexity analysis without freezing
  • Two project explanations (2 minutes each)

30 days out: weekly full OA-style mocks; close weak DSA patterns; draft STAR stories.

7 days out: alternate mock / review days; re-solve misses cold; no new patterns.

Day before: skim notes, check machine/network/ID logistics, sleep.

  1. Failing OA test cases, or LP stories that are vague and unmeasurable - fix this first
  2. Preparing only interviews while failing Amazon’s first round
  3. Collecting notes without timed mocks
  4. Listing five frameworks on the resume and defending none
  5. Changing language/stack one week before the drive
  6. Silent coding - interviewers cannot grade your head
  7. Memorizing solutions you cannot adapt

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Next step: Run one timed mock this week that matches Amazon’s first round (OA coding), then build the weeks around your weakest section - not around what is most fun to study.