Akash Chaudhary

Here's my Google SWE interview experience. 🔹 Screening Round This was a 45-minute eliminatory interview. The problem required a sliding window approach, with a follow-up question that I solved using a hashmap. A complete, working code solution in a Google Doc was expected. 🔹 Onsite 1: Data Structures & Algorithms This round focused on a binary tree problem, this was a variation of the Lowest Common Ancestor (LCA). 🔹 Onsite 2: Data Structures & Algorithms The second technical onsite involved a graph traversal problem that can be best solved using a multi-source Breadth-First Search (BFS). 🔹 Onsite 3: Googlyness & Leadership This was the behavioral round, focusing on situational and leadership-based questions. I drew upon my past experiences to navigate the discussion. 🔹 Onsite 4: Data Structures & Algorithms This round was particularly interesting. I was presented with a complex problem that required multiple stages of optimization. The final, most efficient solution involved a combination of a Doubly Linked List and a Hashmap. Overall, It was a great experience that truly tested the depth of understanding of Data Structures & Algorithms. A key takeaway was the emphasis on clear communication and articulating the thought process behind every decision, not just arriving at the final answer. For anyone preparing for similar roles, I'd highly recommend mastering the fundamentals and practicing how to verbalize your problem-solving approach. #Google #SWE #InterviewExperience #FAANG #CodingInterview

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Your friend take 3 mins, read the problem 3x, and then code and end up cracking SDE-1 Microsoft.  You read it once and start coding, you’re not the same bro. Your friend take the first 15 mins to decide approaches for questions and end up SDE-1 Amazon Meanwhile, you’re on your 2nd problem with no thought given, you’re not the same bro. Your friend see the problem & can immediately see the type of pattern on and end up SDE-1 Uber You see the problem and think, “ye meine pehle kiya tha kya”, you’re not the same bro. 95% of people who appear for the first DSA rounds at PBCs offering 25-30LPA get rejected there itself. The biggest factor for that is your preparation method for DSA. The wrong way will lead you: - force yourself to memorize solutions - panic if the problem is new and unseen - mess up constantly during coding live in an interview The right way will lead you: - be calm, focused, and use your time - never panic cause you know the patterns - never force cram anything, purely understand - impress the interviewer with your organized thinking A person who does pattern-based learning >>> will always win when compared to one who doesn’t. I know the right way, because I did the exact thing and it led me to results and so do all the other folks who’re getting results. It all starts with a good preparation strategy, one of the best resources you can go for is this DSA pattern cheat sheet that I’ve heard about from 100s of students out there. Check out the product here- https://lnkd.in/g_GkJUsN

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I’ve sat in interviews at 3 MAANGM companies (Google, Microsoft, Amazon) …and here are 3 things you NEED to know before your next interview 👇 (Esp. if you’re preparing for mid-to-senior-level SDE roles at top PBCs, here’s what I’ve learned along the way ✅) 💡 TIP #1: Give Data Structures & Algorithms (DSA) fundamentals PRIORITY. → Most tech giants, esp. Google, expect you to be strong in Arrays, Strings, Trees, Graphs, and DP. → Don’t just solve random problems. Instead, focus on mastering core patterns, Sliding Window, Binary Search, DFS/BFS, Trie, DP state transitions. 💡 TIP #2: Don’t think Behavioral Rounds are “OPTIONAL” At PBCs like Amazon, your real contributions and leadership will matter. So always quantify your impact → “Led a team of 4 engineers to reduce API latency by 30%” is far better than “Worked on APIs”. 💡 TIP #3: System Design will become UNAVOIDABLE (even mid-level) Interviewers will expect you to design scalable, reliable systems, and explain tradeoffs clearly, especially at Microsoft. Practice structuring your thought process ⬇️ → Start with requirements → High-level architecture → Data modeling → API contracts → Scalability challenges. These actionable tips can help you switch to MAANG-level PBCs, so if you’re working a 9-5 and struggling to prep for your next big role… I highly recommend giving Bosscoder Academy a try. 🔗 Explore their programs here: https://bit.ly/4gq7uIp They’ve already helped 2,200+ engineers land roles in top PBCs with structured prep in DSA, System Design, and Full Stack, 1:1 mentorship, mock interviews, resume support, and 100% job switch guidance. #sdeprep #systemdesign #interviewtips #tech #jobswitch #maang #pbcs #collab #interviews #jobs #dsa #resume

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From SDE → ML Engineer at Intuit (30 LPA) 🚀 A friend recently switched to a Data Scientist role and shared how challenging it felt, despite years in tech. New tools, new expectations, and a whole new interview process. Here’s how he prepared: ✅ Focused more on projects than just theory ✅ Revisited Python, stats, and ML basics properly ✅ Learned to explain models, not just build them ✅ Took mock interviews with senior ML engineers Initially, he struggled to even get shortlisted with his engineering experience, but after connecting with Senior Data Scientists who had made similar transitions, he ended up cracking 4 offers. 🎉 If you’re also aiming for a big switch, don’t wait for the perfect opportunity. Focus on your prep, upskill, and practice with senior professionals who've done it themselves. ↳ Connect with them for FREE here: https://lnkd.in/gN2XQiRc They’ll guide you with upskilling, resources, mock interviews, resume support, and projects—everything you need to switch faster to your dream role. ✨💪 #domainswitch #datascience #softwareengineer #paidpartnership #successstory #interviewprep

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* Whether it’s Leetcode, GFG, or Blind 75 → At its core, it’s about understanding *why* the solution works, not just what the code is. * Whether you mug up Google’s “most asked” list or crack 200 Amazon questions → At its core, it’s about thinking on your feet, not recalling a pattern from memory. * Whether you’re prepping for system design at Uber or DSA at Microsoft → At its core, it’s about breaking down new problems, not just repeating what you practiced. * Whether you face a friendly interviewer or a senior who digs deep → At its core, it’s about communicating your thought process, not just spitting out code. * Whether you’ve solved 500 questions or just 50 → At its core, it’s about the fundamentals, problem solving, clear thinking, and adaptability. Once you’ve given enough interviews at FAANG+ companies, have faced rejections, and spent enough time in the industry, you realize the #1 mistake in coding interviews is thinking you can just memorize the answers. You can’t predict the exact questions. You can’t game the system. But you can train your brain to solve any problem, no matter how unfamiliar. * Practice talking through your logic, not just typing. * Try whiteboarding without syntax help. * Focus on understanding patterns, not memorizing them. Tools and question banks will keep changing. Deep problem-solving skills last your whole career. If you’re still stuck memorizing, you’re setting yourself up to fail when a curveball comes. Don’t memorize, master the fundamentals. That’s how you truly stand out.

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