Ketul Mehta

It was 8:42 PM at the Amazon office when Priya, a senior engineer, noticed a Slack message from Raj, the newest backend SDE on her team. “Hi Priya, the orders API endpoint you own is suddenly returning 503s after my changes. Could you help me debug? Sorry for the late message.” Priya hesitated for a second. She’d spent months refining that endpoint, handling edge cases, scaling for Prime Day traffic, even documenting the entire flow for new team members. She remembered her own early days, when breaking something felt terrifying, and the seniors weren’t always patient. For a split second, Priya wanted to reply, “It was working fine earlier. Did you check the wiki?” But she didn’t. She joined the call. Raj was clearly stressed, walking through his recent commits. First month at Amazon, production issue, and it was late. Priya listened, asked focused questions, and together they tracked down a missing API key in the environment config. Raj sighed, “Thank you, Priya. Didn’t mean to break anything, just trying to add new promo logic.” Priya replied, “No worries. Bugs happen to all of us. What matters is catching them fast. I’d always rather have a teammate who asks for help than one who hides a problem.” The next morning, Priya shared a quick note in the team channel: > “Thanks to Raj for surfacing the issue quickly and collaborating on the fix. These things happen, what counts is how we respond.” And as she updated her notes, Priya reflected: → Being smart is good but being reliable, calm, and collaborative under pressure is what builds trust. → The most critical projects rarely go to the “lone genius.” They go to the person the team can depend on, day after day. Over time, more teammates started coming to Priya for tricky launches, because she was steady, approachable, and always showed up when it mattered. Because in the long run, that’s what makes you the engineer everyone trusts to deliver. And that’s the reputation that really opens doors.

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If I had a system design interview tomorrow at Google, this is exactly how I’d approach it. (This framework helped me crack 3 FAANG+ companies in the past, including Amazon.) Most engineers fail system design interviews not because they lack knowledge but because they lack structure. You don’t need to memorize 100 architectures. You need a structured and easy-to-apply approach that works every time. Here’s how I break it down: 1/ Clarify the Problem Before Writing Anything - System design interviews aren’t about throwing buzzwords—they’re about trade-offs. - Start with scoping → Are we designing just one feature or the entire system? - Ask constraints upfront → How many users? Read/write ratio? Latency requirements? - Define success criteria → What matters most? Scalability? Cost? Low-latency? Most candidates assume things and jump into solutions. I make sure I know what we’re solving before I even start. 2/ Define Functional & Non-Functional Requirements Clearly - Functional: What features does the system need? - Non-functional: What are the performance expectations? - What’s the biggest technical challenge? (This helps guide the discussion.) Example: If we’re designing YouTube, is the focus on video uploads, recommendations, or live streaming? Each has a different set of constraints. 3/ Estimate the Scale & Plan Capacity Like an Engineer - Users per second? Requests per second? - Storage needs? If we store 10MB per user and have 100M users, what does that mean? - Throughput? Can a single database handle the load, or do we need sharding? Most candidates throw random numbers. I do quick, back-of-the-envelope calculations to validate my assumptions. 4/ Break the System into Core Components (High-Level Design) - Define the major building blocks → API Gateway, Load Balancer, Service Layers, Databases. - Don’t overcomplicate. Simple and scalable always wins. - Clearly define the interactions between services. If I’m designing a messaging app, I break it down into: — User Service (auth, profiles) — Messaging Service (storing chats) — Notification Service (real-time updates) — Media Storage (for images, videos) Each has different constraints, so I build around what’s most important. Continued Here: https://lnkd.in/eJ2T966N

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I interviewed at Google, Uber, Walmart, Amazon and several top startups (a total of 60+ interviews) during my job search from March to June 2025 before joining Atlassian as a Principal Engineer. Here’s what each experience taught me. If you’re prepping for a switch, I hope this gives you clarity on what to expect (and how to survive the roller coaster): [1] Google (L5) ○ Offer Verdict: Not offered ○ Both rounds were deep dives into trees/BSTs and circular buffer implementations. ○ I ended up over-complicating my code, focusing on perfect edge-case handling instead of moving forward. ○ Lost track of time, which cost me the chance to showcase my strengths. ○ Sometimes, you need to show breadth before depth. [2] Uber (L5a) ○ Offer Verdict: Not offered ○ Honestly, the environment was tough: the interviewer was rigid and not open to dialogue. ○ Started with a brutal BST cost optimization DP, hit a wall early and couldn’t recover. ○ Only got momentum on the second question, but the clock had already run out. ○ Not every room is fair, but you’ve got to play the hand you’re dealt. [3] Amazon (L6) ○ Offer Verdict: Offered ○ From the start, leadership principles were baked into every question. ○ Coding was challenging, but behavioral rounds tested my ability to own up to mistakes and learn from failure. ○ The bar-raiser loop pushed for specifics, what did I do, how did I decide, what did I learn? ○ At this level, they want to see if you’ll drive change, not just write code. [4] Walmart (Staff) ○ Offer Verdict: Offered ○ Coding round seemed basic at first, until edge cases and perf requirements kicked in. ○ Subsequent rounds focused on both granular (LLD) and high-level (HLD) architecture. ○ Hiring Manager discussions went deep into how I handle ambiguous requirements. ○ The difference? Anticipating what can go wrong and showing how you think in the grey areas. [5] Atlassian (Principal) ○ Offer Verdict: Offered ○ The bar here was full spectrum: system design, core DSA, LLD, behavioral, and true leadership interviews. ○ I was tested on scale, “what if usage spikes 100x?”, and had to justify every major design call. ○ What stood out: They valued holistic, end-to-end thinking, not just technical correctness. [6] Salesforce (LMTS) ○ Offer Verdict: Offered ○ Hackerrank and coding rounds were rigorous but fair. ○ The real difference was in the design interviews, lots of follow-ups, real curiosity about my decisions. ○ In-person Hiring Manager round checked for real fit and long-term vision. ○ You can sense when a company genuinely wants to know how you think. Rest 2 are in the comments… Job search is less like flipping a coin, and more like running a marathon with hurdles, some you clear, some you crash into, but you have to keep moving. The more finish lines you cross, the higher your chances of success. Every interview teaches you something. Eventually, persistence beats luck. Good luck, see you on the other side.

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The first SDE-2 absolutely nailed the system design round. The question was: Design a live streaming system. The second SDE-2 was asked to Design Google Drive. He did well, spoke about trade-offs, but missed one important detail: chunking the file, especially for large uploads. Yet, the second engineer got the job. These are from real interviews I took around 4 months ago. You might ask: Why? Only one reason, the second one nailed the behavioral questions like a boss. The question was about working on a project with tight timelines. The first SDE-2 (subtly) blamed the external team’s API for delays, which led to tight project deadlines. The second one, on the other hand, shared a story about how he helped his manager prioritize requirements to navigate the crunch. That’s how important behavioral interviews are. Yet, 90% of SDEs leave them to luck. If everything else is equal: - DSA (both solved the coding problems), - LLD (designed with solid object-oriented principles), - HLD (covered all the P0 functional and non-functional requirements) then your behavioral answers become the deciding factor. Yes, the second engineer missed the file chunking detail. But it wasn’t a critical red flag. He covered all other parts well and crushed the behavioral round. As long as you're working with humans (no matter how many), you’ll be judged on your behavioral skills. Call them soft skills, leadership skills, whatever you like, but you should prepare them well in advance. You can start preparing for behavioural interviews right away, with these 5 MUST read behavioural interview posts I wrote. (tip: save this post for later, as it may take some time to complete all of them) [1] How to answer any behavioural interview question https://lnkd.in/gH3N8b5q [2] 4 step guide for behavioural interview preparation in 3 hours https://lnkd.in/gccxG3MP [3] How to create 10+ stories for your past projects https://lnkd.in/g4nv_jqU [4] How to answer a failure story? https://lnkd.in/gtN-Dfuv [5] 10 behavioural interview mistakes to avoid at all cost https://lnkd.in/gpupvYVs If you’re preparing for mid-senior SDE or EM roles and need dedicated help with behavioral interview prep, DM me COACH.

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If you want to become better at system design rounds, definitely read these 10 case studies by Neo Kim. I am 100% sure, they will make you smarter for your next interview.  1/ How Meta Achieves 99.99999999% Cache Consistency: → https://lnkd.in/e88kUZAm 2/ How Uber Computes ETA at Half a Million Requests per Second: → https://lnkd.in/eVKV2ePC 3/ How PayPal Was Able to Support a Billion Transactions per Day With Only 8 Virtual Machines: → https://lnkd.in/eqcb7MpP 4/ How YouTube Was Able to Support 2.49 Billion Users With MySQL: → https://lnkd.in/efmJw4Dx 5/ How WhatsApp Was Able to Support 50 Billion Messages a Day With Only 32 Engineers: → https://lnkd.in/gRqBgXfc 6/ How Uber Finds Nearby Drivers at 1 Million Requests per Second: → https://lnkd.in/eeqH9Hjh 7/ How Stripe Prevents Double Payment Using Idempotent API: → https://lnkd.in/erMkqwq4 8/ How Google Ads Was Able to Support 4.77 Billion Users With a SQL Database: → https://lnkd.in/efnSvwJp 9/ How Amazon S3 Achieves 99.999999999% Durability: → https://lnkd.in/eutGiK35 10/ How Slack Works: → https://lnkd.in/eATMDjrK

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What I thought Software Engineering was in 2021 vs What I think as a Senior SWE at Walmart in 2025: => In 2021 as a junior developer: - Seniors have all the answers - Impact = number of tickets closed - The best engineers are the smartest - Asking questions makes you look junior - You should always say yes to show initiative - Writing clean code is the most important part of the job - If you’re not shipping code every day, you’re not growing - Promotions happen when your manager notices your effort - You need to fix everything yourself to be seen as reliable - Whoever solves the ticket fastest is the best engineer - Hard work will automatically get recognized - Learning more frameworks = growth - Documentation is a “nice-to-have” - If code works, it’s good enough - Meetings are distractions => In 2025 as a Senior SWE: - Asking good questions is a senior-level skill - Visibility + clarity = recognition (not effort alone) - Impact = clarity, velocity, and outcome, not volume - The right meetings build alignment and unblock progress - Depth in fundamentals beats hopping between frameworks - The best engineers make the team faster, not just themselves - Thinking, designing, mentoring, debugging, that’s growth too - Writing maintainable code is more valuable than just clean code - Knowing who to loop in is as important as knowing what to fix - Promotions happen when you start operating at the next level - Strategic “no” is sometimes more powerful than blind “yes” - Seniors ask better questions not give perfect answers - The best engineers are calm, curious, and consistent - If your code confuses someone else, it’s broken - Documentation is a force multiplier In 2021, I thought software engineering was about building things. In 2025, I’ve learned it’s about enabling others to build better, faster, and safer. Follow me Akash Sinha for more content on SW Engineering, How to grow as a SWE and AI

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🎯 Master System Design Interviews: 50 Questions That Separate Junior from Senior Engineers As a technical recruiter, I can tell you that system design knowledge isn't just about getting hired - it's about being prepared for real-world engineering challenges. Today, I'm sharing a game-changing resource that could transform your interview preparation. 🔑 Why This Matters: The difference between a $1XXK and $2XXK+ offer often comes down to system design expertise FAANG companies heavily emphasize system design in their interviews These questions reflect actual scenarios you'll face in production environments 📋 What's Included: 50 carefully curated system design questions Real-world examples from companies like Netflix, Uber, and WhatsApp Detailed solutions and architectural approaches Progressive difficulty levels from foundational to complex systems 🎯 Key Categories: Fundamental Concepts API Gateway vs Load Balancer Microservices vs Monolithic Architecture Horizontal vs Vertical Scaling Popular System Designs URL Shortener Chat Applications Video Streaming Platforms Social Media Feeds Advanced Scenarios Distributed Systems Real-time Processing High-Availability Architecture 💡 Pro Tips: Practice explaining your thought process Focus on scalability and reliability Consider trade-offs in your solutions Master the fundamentals before tackling complex designs 🔍 Resources Included: Detailed explanations Architecture diagrams Best practices Common pitfalls to avoid Ready to level up your system design skills? Download the complete guide (link in comments) 📚 #SystemDesign #SoftwareEngineering #TechInterviews #Engineering #FAANG #TechCareers #SoftwareDevelopment #CodingInterview Call to Action: Like and share if you found this valuable Comment with your favorite system design question Follow for more engineering insights Remember: Great system design skills aren't built overnight. Start practicing today! 💪

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After reviewing 200+ applications over the last few months across Amazon and Apple, here are the patterns that separate strong candidates: 🎓 Fresh Graduates: Sharing insights from screenings 📋 Resume/Profile Fundamentals: • Show impact with duration context: "Led 6-month capstone project that improved user engagement by 35%" beats "Worked on a project" • Be selective with technical skills: List 2-4 languages/tools you can confidently discuss, not every technology you've encountered or heard about • Depth over breadth: Better to show mastery of some technologies (like React, Docker, Spark etc.) than list 15 frameworks superficially 🔍 The Reality Check: Interviewers *will* dig deep into every skill you list. If you've only heard of Kubernetes or used Docker once in a tutorial, leave it off. They are trained to spot knowledge gaps quickly, and overselling hurts more than being honest about your learning journey. Present your skills authentically and showcase your achievements—interviewers are looking for overall fit, skills, and learning capabilities. 🌐 Expanding Your Reach: • Engage authentically in tech communities—quality interactions matter more than follower count • Share your learning process, not just achievements • Connect meaningfully with engineers (research their work, ask thoughtful questions) 💡 What Actually Matters: • Clear progression and growth mindset • Honest self-assessment of skills • Projects that show you can see something through to completion • Evidence of collaboration and communication skills 🎯 Bottom Line: Your curiosity and potential matter more than knowing every technology. Focus on demonstrating solid fundamentals and passion for solving problems. #FreshGraduates #EngineeringJobs #ResumeAdvice #TechCareers #HiringTips

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Your PR got blocked during the code review.  You have about 20 comments, most of which are minor suggestions.  The deadline is near, and your manager just asked for an update. Here’s what you shouldn’t do in this situation: - Take it as a personal attack. - Get defensive or start justifying every little thing. - Respond emotionally or rush to reply. - Blame others for missing details. - Drag out the discussion in comments. Instead, do this: - Stay calm and treat it as constructive feedback. - Go through the comments with an open mind. - Ask for clarification where needed. - Address the issues in a clear, focused way. - Propose a quick call to resolve any bigger concerns. Comments are great for feedback and documenting ideas, but they don’t communicate the tone or how you want to say it. While working in a team, it’s not just about what you say but also how you say it. A short conversation can clear up misunderstandings in minutes that might take hours to hash out through written replies. Sometimes, a quick chat leads to a much smoother and faster resolution.

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