How to Prepare for Amazon, Google, Microsoft Interviews

Alright, so you want to crack an interview at one of the big ones. Amazon, Google, Microsoft. Maybe you’ve been thinking about it for a while, maybe someone at work just got an offer from Google and now it’s all you can think about. Either way, you’re here, and I can probably help.

I’ve been through this process myself — not at all three companies, but at two of them, and I’ve helped enough friends and colleagues prep that I’ve seen a pretty wide range of outcomes. Some people get in on their first try. Most don’t. Some people study for six months and still get rejected, then try again and succeed with three months of different preparation. The process is somewhat random, I think, but there’s a lot you can do to shift the odds in your favor.

Let me break down what I actually know about each company’s process and how to prepare, without sugarcoating the parts that are just straight-up hard.

How These Interviews Generally Work

All three companies follow a similar overall structure, with company-specific variations that I’ll get into. The general pipeline goes like this:

Step 1: Application or referral. You either apply through the careers page or (much better odds) get referred by a current employee. More on this later.

Step 2: Online Assessment (OA). Not always, but common for campus hiring and some experienced roles. Usually 2-3 coding problems on a platform like HackerRank. Time-limited, typically 60-90 minutes.

Step 3: Phone/video screening. One or two rounds of coding over video call. An engineer asks you to solve problems in a shared coding environment. 45-60 minutes each.

Step 4: On-site (or virtual on-site). The big day. 4-5 back-to-back interviews covering coding, system design (if you’re experienced), and behavioral questions. Takes most of a day. This is where it’s decided.

The whole process, from application to offer (or rejection), typically takes 4-8 weeks. Sometimes longer if there are scheduling delays or if you’re put in a “holding pool.” The timeline can feel agonizing, but that’s standard.

Amazon: Leadership Principles Are Not Optional

Amazon’s interview process is distinct because of how heavily it weighs behavioral questions tied to their 16 Leadership Principles (LPs). At most companies, behavioral rounds are the warm-up before the “real” technical rounds. At Amazon, behavioral questions carry equal or sometimes more weight than coding. People who nail every coding problem but bomb the LP questions get rejected. I’ve seen it happen.

The Leadership Principle Prep

You need to prepare STAR stories (Situation, Task, Action, Result) for at least the most commonly tested principles. From what I’ve seen and heard from people who’ve interviewed there, these come up the most:

Customer Obsession. Tell me about a time you went above and beyond for a customer (or user, or stakeholder). What was the situation, what did you do, and what was the outcome?

Ownership. Describe a time you took responsibility for something outside your formal scope. Bonus points if it was messy and you didn’t have to do it.

Bias for Action. When did you make a decision with incomplete information? What happened?

Dive Deep. Give an example of a time you dug into the details of a problem rather than accepting the surface-level explanation.

Disagree and Commit. When did you disagree with a decision but support it anyway once it was made?

Prepare 2-3 STAR stories for each principle. Make them specific. Include numbers. “I improved the response time” is weak. “I identified a bottleneck in our database queries that was causing 3-second load times, rewrote the queries to use indexed columns, and reduced response time to 400ms” is strong. Amazon interviewers are trained to follow up with “Tell me more about that” and “What specifically did YOU do?” so your stories need to be genuinely yours, not team accomplishments vaguely attributed to yourself.

Amazon Coding

Medium-difficulty LeetCode style problems. Arrays, strings, trees, graphs, and dynamic programming show up the most. Amazon doesn’t typically ask the hardest problems (that’s more of a Google thing), but they want clean, working code in the 45-minute window. Practice 150-200 problems on LeetCode with a focus on Amazon-tagged problems.

One thing about Amazon: they care about your approach more than some companies. Think out loud. Talk through your brute force approach first, then improve it. Ask clarifying questions before diving in. This mirrors their internal culture of “working backwards” from the problem.

Amazon System Design

For SDE-2 and above (roughly 3+ years experience). Common questions include: design a URL shortener, design Amazon’s product recommendation system, design a notification service, design an e-commerce order processing pipeline. The interviewer wants to see that you can think about scale (millions of users), make tradeoffs (consistency vs. availability), and design APIs and database schemas that make sense.

The Bar Raiser Round

Unique to Amazon. A senior engineer from a completely different team evaluates your overall caliber. This person has veto power over the hiring decision. The Bar Raiser interview mixes behavioral and technical questions and is specifically designed to assess whether you’d raise the average quality of Amazon’s engineering team. It’s probably the most unpredictable round because the questions can go in any direction.

Google: The Coding Standard Is Just… Higher

Google’s interviews are widely considered the most technically challenging among the three. The emphasis is on algorithmic problem-solving, mathematical thinking, and code quality. You’re expected to not just solve the problem but solve it optimally, explain the time and space complexity, handle edge cases, and write clean code.

Google Coding Prep

Practice hard-level LeetCode problems, not just medium. Google frequently asks problems involving graph algorithms (BFS, DFS, Dijkstra, topological sort), dynamic programming (both classical and non-obvious DP problems), string manipulation with tricky constraints, segment trees and binary indexed trees (less common but they appear), and math-based problems requiring creative approaches.

Google interviewers write their own problems sometimes, so you might face something you’ve genuinely never seen. That’s by design — they want to see how you think through novel problems, not just how well you’ve memorized solutions. This is why understanding patterns matters more than memorizing specific problems.

Target 250-300 LeetCode problems with a heavy emphasis on Medium and Hard. Google-tagged problems on LeetCode and problems from Codeforces (rated 1400-1800) are good practice.

Google System Design

For L4+ roles (roughly 4+ years experience, though L4 can include strong candidates with 2-3 years). Common questions: design Google Maps navigation, design YouTube’s video processing pipeline, design a web crawler at Google scale, design Google Docs collaborative editing.

Google system design interviews emphasize scalability (think billions of requests), consistency models, distributed systems concepts, and data storage strategies. They want you to think about what happens when things go wrong — server failures, network partitions, data center outages. Read about Google’s actual infrastructure (Bigtable, Spanner, MapReduce, Colossus) to understand the scale they operate at.

Googleyness and Leadership

Google has a behavioral component too, though it’s weighted less heavily than Amazon’s LP rounds. They evaluate “Googleyness” — which from what I can tell means intellectual curiosity, comfort with ambiguity, collaborative mindset, and an ability to challenge ideas respectfully. Prepare examples of times you worked well in a team, dealt with unclear requirements, helped someone grow, or challenged a decision constructively.

The Hiring Committee

Unlike Amazon and Microsoft, Google uses a hiring committee that reviews all interview feedback after your on-site. Your interviewers don’t make the hiring decision directly — they write feedback, and the committee decides. This can work in your favor (one bad round doesn’t automatically sink you) but also means the process takes longer and feels opaque.

Microsoft: Structured and Clear, But Don’t Underestimate It

Microsoft’s interviews feel slightly more approachable than Google’s, but that doesn’t mean they’re easy. The process is more structured, the problems tend toward medium difficulty, and there’s a strong emphasis on practical engineering and clear communication.

Microsoft Coding

Medium-difficulty problems with an emphasis on clean implementation. Linked lists, trees, sorting algorithms, hash maps, and object-oriented design questions are common. Microsoft cares about code quality — meaningful variable names, proper error handling, clean structure. They’d rather see a well-implemented medium solution than a sloppy hard solution.

Practice 150-200 LeetCode problems. Microsoft-tagged problems are helpful. Also practice writing code on paper or a whiteboard (not just in an IDE with autocomplete) because some Microsoft rounds still use whiteboard-style coding.

Low-Level Design (LLD)

Something Microsoft asks more than the other two: design a class hierarchy for a specific system. Design a parking lot management system. Design a library book management system. Design chess. Design an elevator system. These object-oriented design questions test your ability to identify classes, relationships, and design patterns. If you haven’t done much OOP design, practice 8-10 classic LLD problems before your interview.

System Design for Senior Roles

Similar to Amazon and Google — large-scale distributed system design. Design a chat application like Teams. Design a cloud file storage system. Design an email delivery system. The expectations are slightly less “Google-scale” but still demanding.

The “As Appropriate” (AA) Round

Microsoft’s equivalent of Amazon’s Bar Raiser. A senior hiring manager (often at the Director level) conducts this interview, which focuses on behavioral and cultural fit alongside some technical assessment. This person has final say on the hire/no-hire decision. The AA round tends to be more conversational than the technical rounds — they want to understand how you think, how you work with people, and whether you’d thrive at Microsoft.

A 3-Month Prep Plan That Actually Works

Assuming you’re working full-time and can dedicate 2-3 hours daily plus weekends.

Month 1: Build the Foundation

Revise data structures and algorithms from scratch. Don’t skip this even if you think you remember everything — you probably don’t. Arrays, strings, linked lists, stacks, queues, trees, graphs, heaps, hash maps, tries. For each data structure, understand the core operations and their time complexities.

Start solving LeetCode problems: 5-6 per day, beginning with Easy. The goal isn’t speed yet — it’s rebuilding pattern recognition. When you solve a problem, don’t just move on. Read the top-voted solutions. Understand why their approach is better. Internalize the patterns.

Begin reading system design material. “System Design Interview” by Alex Xu (Volume 1 and 2) is the most efficient resource I’ve found. Read one chapter per night.

Month 2: Push Harder

Shift to Medium and Hard LeetCode problems. Focus on company-tagged problems for your target company. If you’re stuck on a problem for more than 40 minutes, look at the solution, understand it, and redo it from scratch the next day without looking. This “learn and redo” approach builds understanding faster than either pure grinding or pure solution-reading.

Practice system designs. Spend 35-40 minutes designing a system on paper, then compare your design with published solutions. Focus on: defining requirements (functional and non-functional), estimating scale, designing APIs, choosing databases, drawing the architecture, and discussing tradeoffs.

For Amazon specifically: write out your STAR stories. Physically write them. Refine them. Practice telling them out loud. Time yourself — each story should take 2-3 minutes.

Month 3: Simulate and Polish

Mock interviews. This is non-negotiable. Solving problems alone is very different from solving them while someone watches and asks questions. Pramp is free and good for coding mock interviews. InterviewBit has a structured program. If you can afford it, interviewing.io pairs you with engineers from top companies for realistic practice.

Do at least 10-15 mock interviews across coding and system design. After each one, write down what went well and what didn’t. Identify your weak areas and spend focused time on them.

Do company-specific preparation. Each company has quirks: Amazon loves DP and LP stories, Google loves graph problems and optimality proofs, Microsoft loves clean OOP design. Allocate your last 2-3 weeks to the specific company you’re interviewing at first.

Resources That Indian Engineers Actually Use

Striver’s SDE Sheet. 180 problems curated for FAANG prep. Wildly popular in India and for good reason — it covers every important topic efficiently. Available on takeuforward.org.

GeeksforGeeks. Best for concept explanations and company-specific question archives. The editorial quality varies, but the breadth of content is unmatched for Indian tech interviews.

NeetCode. Organized by pattern (sliding window, two pointers, backtracking, etc.). His YouTube explanations are clear and well-structured. Good for building pattern recognition.

Gaurav Sen’s YouTube channel. System design explanations that are visual and intuitive. Particularly good for understanding distributed systems concepts.

“Grokking the System Design Interview” on Educative. Paid but worth it if system design is your weak area. Structured, thorough, and covers the most commonly asked designs.

LeetCode Discuss. After solving (or failing) a problem, read the discussion threads. People post their interview experiences, alternate solutions, and insights that you won’t find in the editorial.

Blind. Anonymous forum where tech employees share salary data, interview experiences, and company-specific tips. Take everything with a grain of salt (it’s anonymous for a reason), but the salary data and interview reports are generally reliable.

Indian tech Twitter and LinkedIn. People share their interview experiences, preparation strategies, and even specific questions they were asked. Follow engineers at companies you’re targeting. The Indian tech community on these platforms is surprisingly generous with information. I’ve seen entire interview debriefs posted publicly within days of someone’s interview.

Getting the Interview in the First Place

All the preparation in the world doesn’t help if you can’t get an interview. Two strategies that work:

Referrals. By far the most effective way. A referred resume gets viewed, period. Without a referral, your resume competes with thousands of others. Find current employees on LinkedIn — alumni from your college, people from your current company, connections of connections. Send a polite message explaining your background and asking if they’d be willing to refer you. Most people are open to it because companies pay referral bonuses of 50K-2 lakhs per successful hire.

Competitive programming profiles. Having a good rating on Codeforces, CodeChef, or LeetCode makes your profile visible to recruiters from these companies. Google in particular has historically sourced candidates through competitive programming communities.

One Last Thing

I want to tell you something a friend told me after I got my first rejection from a big tech company. I was pretty messed up about it — months of preparation, felt like I’d thrown it all away. And he said, “You know, the guy who interviewed you? He probably failed his first attempt too.”

I looked it up later. A surprising number of engineers currently at Google, Amazon, and Microsoft were rejected on their first application. Some on their second. The process has randomness built in — which interviewer you get, which problems they pick, whether they’re having a good day, whether your brain cooperates under pressure that particular morning. A rejection doesn’t mean you’re not good enough. It sometimes just means the dice didn’t roll your way that day.

The engineers who make it are usually the ones who apply again.

Most companies have a cooldown period after rejection — typically 6 months for Amazon, 12 months for Google, and 6-12 months for Microsoft. Use that time. Figure out where you fell short, work specifically on those areas, and come back stronger. A rejection letter isn’t a permanent verdict. It’s a timestamp on one performance on one day. Your next attempt can be completely different.