Lessons Learned from a Microsoft Interview

When I interviewed candidates for our team at Microsoft, one thing always set the best apart. Specificity. Their answers showed that they did their research. They knew exactly why we were hiring and how their background fit — and they gave specific examples to prove it. This was one of the most consistent things across our best hires, so much so that I actually ended up using it as a screening test. If I could replace Microsoft with a competitor (Google, Amazon, etc.) and their answer still worked, it wasn’t a good answer. The people who gave catch-all answers tended to show that they didn't do much research and the convo progressed. Those interviews were generic and boring. But the people who could tell me exactly what was happening and how they could make an impact? Those conversations were a blast and those candidates stood out. So when you’re preparing for your next interview, use this 3 step process: 1. Research the heck out of the company and hiring team 2. Draft up answers that use specific examples and focus on the company’s needs 3. For each answer, ask yourself, “does this answer make sense if I swap in a competitor?” If it does, you need to be more specific! If it only makes sense with your target company, you’re in great shape to crush this thing.

Placing at Microsoft isn’t easy—but it’s absolutely possible with the right steps, patience, and grit. Failures aren’t roadblocks; they’re data points that guide the next attempt. What worked for me from a tier‑3 college to SDE2 at Microsoft: - Build fundamentals daily: DSA, system design, and clean coding habits over shortcuts. - Practice like interviews are a sport: timed problems, mock interviews, and honest retros. - Ship real work: projects, open-source, or internal tools that prove impact and ownership. - Tell your story: show your process, not just outcomes—resume bullets should read like measurable impact. - Embrace failure loops: every rejection is feedback, not identity—iterate faster, not harsher. My experience: - Rejected at a bar-raiser at Amazon—tough, humbling, necessary. It pushed me to fix gaps in structured thinking and trade-off clarity. - Transitioned to SDE2 at Microsoft—moved from backend to AI/Data, built scalable pipelines, and learned to design for reliability at scale. If you’re preparing: - Pick one track for 60–90 days: DSA + 1 system design book + 1 project you can defend end-to-end. - Measure, don’t guess: track topics, mock scores, and patterns you miss under time pressure. - Show your work online: clarity attracts opportunities—your process is your portfolio. Remember: Your first “no” isn’t your last chapter. Keep going. Someone’s “impossible” is waiting for your consistent, boring, daily effort. Full vlog on YouTube— https://lnkd.in/gDfpu-xe #Microsoft #SDE #InterviewPreparation #DSA #SystemDesign #CareerGrowth #TechCareers #Tier3ToTech #KeepGoing #ConsistencyWins #LearnBuildShare

You’re in a system design interview at Microsoft. The interviewer asks you a very tricky problem: “You’ve just designed a global product catalog service for millions of users. To handle traffic, you added Redis caching around your product lookup API. A week later, you start getting weird complaints: – users see stale prices during flash sales. – debugging takes twice as long, can’t tell if a bug is from the DB or cache. – memory usage keeps spiking, and it’s not clear which keys even matter anymore. The interviewer asks: “Caching made your system faster at first, but now it’s causing headaches. How would you decide what to cache, when to cache, and how to keep your cache healthy and correct? What questions should you ask before wrapping everything in Redis? This is how I would tackle it with proper reasoning: Before caching anything, I’d walk through these 7 critical questions: [1] Is the data accessed frequently? Caching makes sense only for data that’s hit often, like product pages requested by thousands every minute. Rarely used data just wastes memory and doesn’t deliver ROI. [2] Is it expensive to retrieve? Caching slow or resource-intensive queries saves real work (think heavy joins, aggregations, external API calls). But for cheap, indexed lookups, the overhead of cache might not be worth it. [3] Is the data stable or volatile? Stable data (like product categories or supported countries) is ideal for caching, safe to keep around. Volatile data (like prices in flash sales or fast-changing inventory) risks staleness; caching here demands strict TTLs or invalidation hooks. [4] Is the data small and simple? Small, flat objects are quick to cache and fetch; big, nested blobs slow everything down and eat up RAM. Don’t cache huge objects if you can break them up or just cache what’s actually used. [5] Does it directly impact user experience? Prioritize caching on the critical path: anything that speeds up what a user sees or interacts with. Background jobs or rare admin tasks? Latency here doesn’t matter much, so skip caching. [6] Is it safe to cache? Caching sensitive or user-specific data without scoping keys risks leaks, never cache what can’t go in a log file. Always use per-user/session keys, encrypt when needed, and set short TTLs for anything risky. [7] Will this scale? Your caching strategy for 1K users can break at 1M — unbounded keys, no eviction, and churn kill performance. Normalize inputs, cap cardinality, and monitor hit/miss/eviction stats as you grow. — P.S. Follow me for more system design insights and check out Layrs - the Leetcode of system design: layrs.me Free to use, no paywalls, and built to help you crack interviews with: - 60+ problems - Interactive canvas - Instant feedback - Easy-to-hard learning flow Join our Discord: https://lnkd.in/gnQ2nGCn

If I lost everything today and had to start from scratch to get back into Microsoft as a software engineer, here’s exactly what I’d do on system design prep,. based on what I know now: I’m currently a Senior Software Engineer at Microsoft (7+ years). I get a LOT of questions about system design interviews, so here’s my full approach. 1. Understand What System Design Interviews Really Test - It’s not about fancy boxes and buzzwords. - You’ll be asked to design a real system (e.g., Uber, Dropbox) on a whiteboard - The goal: Can you break a big problem into working parts and explain your decisions? 2. Brush Up Your Fundamentals - Don’t skip this step. Even seniors forget basic concepts. - Know the differences and use cases for:   - Relational DBs (SQL)   - NoSQL/Document Stores (MongoDB, DynamoDB)   - Key-Value Stores (Redis) - Learn ACID vs BASE. Understand when each makes sense. - Scalability basics: What’s vertical scaling? What’s horizontal? What’s sharding/partitioning? - Networking: You only need to know Application, Transport, and Network layers. (APIs, REST vs gRPC, TCP vs UDP, basic load balancing.) - Latency and performance: Have rough numbers in your head (memory vs disk vs network speeds). Learn to spot and fix bottlenecks. - Fault tolerance: Know how redundancy and replication work. - CAP theorem: Every interviewer expects you to mention consistency, availability, and partition tolerance, and pick the right one for the use case. 3. Pick a Simple, Repeatable Framework for Interviews - Always start with requirements, - functional (features) and non-functional (scale, latency, consistency, etc). - List core entities/tables (users, events, orders, etc). - Map out basic APIs/endpoints needed. - Draw a simple, high-level design: what’s needed for V1 to work at all. - Dive deeper only when the interviewer asks, optimize for scale, speed, or whatever NFR matters most. 4. Focus Your Practice on Common Patterns, Not Random Problems - Don’t get lost in huge lists online. - Instead, focus on core, repeating problems:   1. URL Shortener (Bitly)   2. File Storage (Dropbox)   3. Ticket Booking (Ticketmaster)   4. News Feed   5. Chat System   6. Rate Limiter   7. Message Queue   8. Search Autocomplete   9. Video Streaming   10. Post Search - Work through these one at a time until you can explain every part, storage, traffic, failure, scaling. 5. When Practicing, Use This Cycle - First, try the problem on your own, sketch it on a whiteboard or notebook. - Don’t check solutions right away. Get stuck. Find out what you don’t know. - THEN, look up a detailed solution or watch a video to fill the gaps. - Make notes: What patterns, what components, what trade-offs? - Repeat with the next problem.   (This “struggle first” approach is 10x better than passive reading.) Continued in Comments ↓

After multiple failed interviews despite solid technical skills, I discovered what was missing when a hiring manager told me: "The other candidate asked better questions about our codebase challenges." This changed everything. For my next interview, I researched the company's product and prepared thoughtful questions about their specific technical problems. "I noticed your app has complex user permissions. How do you handle authorization across services?" The interview transformed from an exam into a real engineering conversation. Two days later, I received an offer. Quick Takeaways: 🦄 Research the company's technical challenges before interviewing 🦄 Ask specific, thoughtful questions about their codebase and architecture 🦄 Engage as a curious peer, not just a candidate being evaluated 🦄 Show you're thinking about their problems, not just your qualifications The questions you ask often matter more than the answers you give. This simple shift in approach can make all the difference. 🚀

𝐇𝐨𝐰 𝐈 𝐂𝐫𝐚𝐜𝐤𝐞𝐝 𝐭𝐡𝐞 𝐃𝐒𝐀 𝐑𝐨𝐮𝐧𝐝𝐬 𝐚𝐭 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 & 𝐖𝐚𝐥𝐦𝐚𝐫𝐭 ? A few months back, I found myself stuck in a loop solving random DSA problems every day without any structure. I was busy, but not progressing. That’s when I decided to do something different. Instead of chasing quantity, I started mastering patterns the ones that actually appear in MAANG-level interviews. For three months straight, I practiced with intent: 📍Solving under time pressure. 📍Explaining every line of my code aloud. 📍Handling follow-up questions just like in real interviews. When the interviews came first at Microsoft, then at Walmart, it felt less like an exam and more like a pattern recognition test. Here’s the list of questions I drilled repeatedly 👇 1️/ Strings / Tries: Sliding Window, Minimum Window Substring, Concatenated Words, Word Break 2️/ Searching & Sorting: Kth Element, Median of Two Sorted Arrays, Search in 2D Matrix, Search in Rotated Sorted Array 3️/ Stacks & Queues: Valid Parentheses, Sliding Window Maximum, Queue Using Stacks, Largest Rectangle in Histogram 4️/ Hashing: Two Sum, Subarray Sum Equals K, LCS, Group Anagrams 5️/ Trees: LCA, DFS/BFS, BST Operations, Path Sum 6️/ Greedy: Fractional Knapsack, Job Sequencing, Minimum Coins 7️/ Dynamic Programming: LCS, 0/1 Knapsack, Edit Distance, Coin Change 8️/ Two Pointers: Trapping Rainwater, 2Sum, Container With Most Water 9️/ Graphs: Clone Graph, Number of Islands, Detect Cycle In almost every round, the questions were variations of these exact problems. What made the difference? I stopped treating DSA as a theory and started simulating real interviews: ✔️ Time-bound problem solving ✔️ Explaining my thought process clearly ✔️ Adapting to follow-up questions on edge cases That habit changed everything. If you’re a working professional aiming to transition, DSA, along with guidance. You can checkout Meritshot Academy. https://lnkd.in/gnheR3KQ They will help you with AI-powered doubt resolution and 1:1 mentorship from Microsoft hiring managers plus real interview simulations and Microsoft accredited projects that truly matter. Stop treating interviews as luck. Start preparing like the developers who actually make the jump. #Microsoft #Google #SoftwareEngineering #JobSearch #TechCareers

Microsoft SDE1 Interview Experience my friend had a big dream to work at Microsoft. He had been preparing for a long time, practicing coding problems on a website called Leetcode. One day he finally got their chance to interview at Microsoft for the position of Software Development Engineer (SDE) 1 in India. Background:   - He is a Computer Science student from a Tier-1 college.   - His CGPA is 7.14.   - He has a strong GitHub profile with 2000+ contributions and many projects.  Selection Process:  1. Online Test on Codility:  - Duration: 2 hours   - Questions:    - First question: Easy to medium difficulty    - Second question: Medium to hard difficulty   - Important Tip: Codility doesn’t show the results for hidden test cases, so he double-checked his code before submitting.  2. Technical Round 1:   - The interviewer asked about his projects and past internship experiences.   - They also checked his GitHub profile and were impressed by his skills.   - He was asked about the difference between SQL and NoSQL databases.   - The interviewer then asked his favorite algorithm. He said “Binary Search,” but the interviewer wasn’t fully satisfied, so they discussed it in detail.   - Coding Question: He was asked to solve [Populating Next Right Pointers in Each Node]on Codility.   - He also discussed time and space complexity.   - At the end of the interview, he was asked if he had any questions. This round lasted about 40-45 minutes.  3. Technical Round 2:   - This round was conducted offline, and he had to write code on paper. Some others had this round online.   - The interviewer was a senior manager with 10+ years of experience and was very calm and supportive.   - Question: Implement a Queue using an array with basic functions like push, pop, isEmpty, and isFull, with a fixed capacity \( C \).   - At first, he wanted to use two arrays, but the interviewer asked him to solve it using just one array of size \( C \).   - He then thought of making the array circular, which worked!   - He wrote the solution on paper and made sure to avoid any errors.   - The interviewer reviewed his code and then asked if he had any questions. This round took about 35-40 minutes.  Result:  The next day, he received the news that he was selected! He was overjoyed and couldn’t believe it. Final Thoughts:   This journey wasn’t easy, but his hard work and preparation paid off. He stayed confident and focused, and it led him to success.  Tips and Advice: - Communication: Clearly articulate thoughts and approach during coding problems. - Preparation: Brush up on DSA concepts and practice coding under time constraints. Hope this helps you crack your dream company interview or at least guides you to some level. Feel free to ask anything and share this with your friends who are preparing for FAANG companies ❤️ Follow Vikram Gaur #microsoft #interview

Interviewing for SWE roles at Google, Microsoft, and Goldman Sachs taught me one crucial thing beyond coding & design challenges : While technical skills (Data Structures, Algorithms, System Design) are the entry ticket, demonstrating your thought process and communication under pressure is what often seals the deal. It wasn't just about getting the right answer, but: * Clearly articulating trade-offs (O(n) vs O(nlog n) isn't just theory, why choose one?). * Asking clarifying questions before jumping into code. * Thinking out loud, even when stuck (showing resilience and problem-solving approach). * Discussing testing and edge cases proactively. Different companies might weigh these slightly differently, but they were universally important across my experiences from finance tech (GS) to big tech (MS & Google). I enjoy breaking down the nuances of Software Engineering. Follow me Ashutosh Maheshwari for more such insights. #softwareengineering #systemdesign #techinterviews

How I cracked Microsoft in 3 months (after many rejections) 🔥 In October 2024, I started applying for jobs. Result? Rejections everywhere. Why? I was not strong enough in DSA (Data Structures & Algorithms). Since my background was in Embedded Systems & System Programming, I knew I had to be strong in 👇 • C/C++ Programming • DSA in C • Computer Architecture • Operating Systems • Computer Networking • Linux Kernel • Concurrency & Multithreading 📘 My 3-Month Preparation Strategy Month 1 – Strengthen the Basics • Revised C programming and solved ~40–50 DSA problems (arrays, strings, linked lists). • Covered OS basics (processes, scheduling, memory management). • Studied Networking fundamentals (TCP, UDP, DNS, HTTP). Month 2 – Go Deeper • Advanced DSA: trees, graphs, DP basics (50+ problems). • Studied Computer Architecture (pipelines, cache, memory hierarchy). • Built small System Programming projects (custom malloc, pthreads, sockets). • Learned debugging tools (gdb, strace, perf) to find bugs & memory issues. Month 3 – Interview Prep Mode • System Design: LLD (cache, rate limiter) & HLD (Twitter, URL shortener). • Revised Linux Kernel (drivers, scheduling, system calls). • Covered DBMS basics & SQL queries. • Took mock interviews every week. 💡 Results: • Interviewed at 30+ companies including Nvidia, Qualcomm, Arista, Google, Amazon, Oracle, Intel, Dell, Samsung, Nutanix, IBM and more. • Within just 2 months → 6 offers. • June 2025 → Got the Microsoft offer. • July 2025 → Officially joined Microsoft (SDE2) 🚀 ✨ Lessons I learned: 1. Don’t waste time on 10 different resources pick 2–3 and revise them well. 2. Mock interviews expose your weak points. 3. Rejections aren’t failures they’re free lessons. #Microsoft #Tier3ToMicrosoft #DSA #SystemProgramming #EmbeddedSystems #Linux #Networking #DBMS #SystemDesign #CareerPrep #TechInterviews

Our interviews are designed to evaluate your strong computer science fundamentals and your ability to learn. We focus on two key areas: • Behavioral (Communication and alignment with Microsoft Core Values) • Technical (Problem-Solving Methods, Coding, and System Design) TECHNICAL Problem Solving • Ask Clarifying Questions: Ask clarifying questions upfront to fully grasp the problem before diving into code or design. This avoids wasting time on incorrect assumptions. Interviewers want to see how you break down the information and how you are powering through the problems • Talk about your approach: Show your structured approach to problem-solving rather than trying to guess what the interviewer wants. • Time Management: This is important given the short 45–60-minute interview round. Ensure that there is a strong transition from your problem-solving methods into implementation. Coding Guidelines • Code Cleanliness: Write clean, concise, and bug-free code without using pseudocode. • Language Proficiency: Use your strongest programming language effectively. • Data Structures: Understand common data structures (arrays, strings, queues, linked lists, trees, hash maps, graphs) and their applications. • Algorithms: Review algorithms like recursion and sorting, focus on efficiency (big O notation). Discuss their tradeoffs. • Testing: Test your solutions thoroughly, considering edge and corner cases and potential issues. Make sure you have a test driven solution • Optimization: Provide the most optimal solution first; if not possible, suggest improvements. Do not overcomplicate your solution. System Design Guidelines • Ask clarifying questions, state the functional and non-functional requirements • Understand software design fundamentals such as scalability, distributed systems, SOA, and n-tier architecture. • Familiarize yourself with software system design diagrams and scalability concepts (caching, load balancing, non-relational databases, microservices, and sharding). • Review object-oriented design and Service-Oriented Architecture (SOA) principles.