Leetcode Problem Solving Strategies

I spent 2+ years grinding Leetcode and learning DSA & problem-solving as a CSE student at BITS Pilani. If I had to start again from 0, this is exactly how I’d do it to get hired as a Software Engineer in 2025:  1️⃣ 𝗺𝗮𝘀𝘁𝗲𝗿 𝗰𝗼𝗿𝗲 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮𝗻𝘆𝘁𝗵𝗶𝗻𝗴 𝗲𝗹𝘀𝗲 ○ Before touching random Leetcode problems, I’d master core algorithms like: Binary Search, DFS, BFS, Sliding Window, Two Pointers, Recursion, Backtracking, and Dynamic Programming. ○ The goal isn’t just to “understand” these but to be able to implement them from scratch without hesitation. ○ I’d write each algorithm at least 5-10 times from memory until it becomes second nature.  2️⃣ 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘀𝗼𝗹𝘃𝗶𝗻𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 ○The biggest mistake people make is solving hundreds of random problems without recognizing patterns. ○ 90% of interview problems fall into ~20 coding patterns. ○ Instead of solving 1000+ questions, I’d focus on understanding:    ►How problems within a pattern are similar.    ►What small variations make them different.    ►Which techniques help optimize them.  3️⃣ 𝗿𝗲𝗽𝗲𝗮𝘁 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗷𝘂𝘀𝘁 𝗺𝗼𝘃𝗶𝗻𝗴 𝗼𝗻 ○ Just because I solved a problem once doesn’t mean I’ll remember it. ○ I’d follow this reinforcement schedule for problems I struggled with: Solve it today, solve it again in 1 week and finally solve it again in 1 month. ○This is how I’d make sure I actually retain what I learn.  4️⃣ 𝘀𝘁𝘂𝗱𝘆 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘄𝗮𝘆 ○ When I can’t solve a problem, I’d first struggle with it for at least 30 minutes before looking at the solution. ○ Then, I’d:   ► Write out the solution from memory after understanding. ► Explain why it works in simple words ► (if I can’t explain it, I don’t truly understand it).   ► Look at alternative solutions to compare trade-offs.  5️⃣ 𝗯𝘂𝗶𝗹𝗱 𝗮 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗹𝗶𝘀𝘁 (𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗿𝗮𝗻𝗱𝗼𝗺 𝗴𝗿𝗶𝗻𝗱𝗶𝗻𝗴) ○ Instead of jumping between random problems, I’d follow a structured roadmap like:  ► First 50-60 easy problems → Get comfortable with implementation.   ► Next 80-100 medium problems → Focus on pattern recognition & optimization.   ► Last 30-40 hard problems → Only after mastering the fundamentals.  ○ 150-200 well-selected problems are enough to crack most interviews.  6️⃣ 𝘀𝘁𝗮𝗿𝘁 𝗺𝗼𝗰𝗸 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗲𝗮𝗿𝗹𝘆 (𝗲𝘃𝗲𝗻 𝘄𝗵𝗲𝗻 𝗜 𝗳𝗲𝗹𝘁 𝘂𝗻𝗽𝗿𝗲𝗽𝗮𝗿𝗲𝗱)   ○ Simulating real interviews early helps with time pressure & communication skills.  ○ I’d start setting strict 30-45 min timers on problems to simulate interview conditions.  ○ I’d practice explaining my thought process out loud, since half of the interview is about communication.  (Bonus tip in the comments) ↓

𝗜 𝗵𝗮𝘃𝗲 𝟮𝟳𝟬𝟬+ 𝗰𝗼𝗻𝘁𝗲𝘀𝘁 𝗿𝗮𝘁𝗶𝗻𝗴 𝗶𝗻 𝗟𝗲𝗲𝘁𝗰𝗼𝗱𝗲 𝗰𝗼𝗻𝘁𝗲𝘀𝘁𝘀. 𝗜 𝗮𝗺 𝗮𝗺𝗼𝗻𝗴𝘀𝘁 𝘁𝗵𝗲 𝘁𝗼𝗽 𝟬.𝟬𝟳% 𝗼𝗳 𝘂𝘀𝗲𝗿𝘀. My recommendation on how beginners can start with practicing leetcode - - Start with easy-difficulty problems in the beginning. - If you are able to solve most of the easy-difficulty problems very fast and comfortably, then move to the medium-difficulty problems. This time required for moving from easy to medium will vary from person to person and their current level. Only move to medium ones when you're comfortable with easy ones. - Medium-difficulty is the difficulty level where one should invest the most time in. Because being very good at medium-difficulty problems is good enough for clearing algorithmic rounds of most companies. - Once you start becoming comfortable with medium problems, try tracking the duration of solving the problem. The eventual goal should be to bring this time down to 30 minutes on average. Many interviews are of 45 minutes duration. It's better to have some offset time as it's very likely you will need relatively more time during the actual interview. - Primary Goal while practicing should be to understand the concepts really well. If you have a good understanding, only then you will be able to solve when the problem is presented in an indirect way or with some small variation. - Set a time according to your level, after reading the problem think for that much time, if you still haven't made any progress, then you can check out the hints/solution to understand more. This time should be at least 30 minutes for most people, if this is too less then you aren't giving yourself enough time to think (and this time is where you improve your thinking skills or figure out where your understanding is lacking). - I don't recommend doing topic-wise practice in most scenarios as many times figuring out which approach to use/which data structure to use is one of the most challenging parts of the problem. So if you know the topic beforehand, that's not ideal for learning. For some special cases when you're really weak at a topic or you're learning something new, then solving some topic-wise questions is good for practice. - You can also participate in leetcode contests to test your skills. But don't worry about ratings much, especially when your goal for doing leetcode is doing better in interviews. Focus on learning. - After you're very comfortable with the medium ones, you can start trying some harder ones too in parallel. This will solidify your understanding even more and few companies do ask interview problems compared to that difficulty level. Different strategies are suitable for different people. I think following this strategy should be useful for most people.

I recently had a chance to connect with a Sr. Software Engineer who cracked Google, Meta, Microsoft, and Amazon in the last 10 years of his career. He started at Amazon in 2015 and is now working at Facebook. I asked him one question: How should one start Leetcode in 2025? and got some pointers that I think would benefit everyone.  [1] Stop trying to “cover” Leetcode → The real game is not in “solving 1000 problems.” It’s in identifying patterns behind the questions (sliding window, backtracking, tree traversals, etc.) and understanding when and why to use each. → Each pattern unlocks 10–15 problems. Your goal: See a question and immediately recognize the pattern behind it. [2] Build a rock-solid DSA foundation → Before you even open Leetcode, deeply understand how and why core data structures (arrays, hashmaps, trees, heaps, graphs) work internally. → Don’t just learn how to use them, know their weaknesses, edge cases, and which real-world scenarios they solve best. → For every new topic, write your own implementation (e.g., your own LinkedList, your own Stack, your own Trie) from scratch once, just to internalize the mechanics. [3] Train yourself to break down problems, not just solve them → When you see a new problem, never code immediately. → Spend 5–10 minutes analyzing constraints, drawing diagrams, and “talking out” your approach. → Ask: “What are the edge cases?” “What would brute force look like?” “Can I spot an early optimization?” → In interviews, your ability to explain and reason before coding matters more than racing to a solution. [4] Use problem selection as a learning tool, not a confidence booster → Don’t just grind easy questions to feel “productive.” → Each session, choose a mix: 1 comfort-zone problem to warm up, 2–3 new pattern-based mediums, and 1 “stretch” hard problem, even if you know you’ll struggle. → Log why you struggled and what new pattern or trick you learned (keep a mistake log; review it every week). [5] Build mental maps of tradeoffs and “when to use what” → For every pattern you learn (e.g., sliding window vs. prefix sum, hash set vs. sorting for duplicates), write down:   → What’s the time and space complexity?   → When does this pattern break down?   → When is an alternative more efficient? → Building these comparison instincts is what sets apart those who “grind” Leetcode vs. those who think like strong engineers. Continued In Comments ↓ --- P.S: If you’re currently preparing for DSA, HLD, and LLD. Check out my one-stop resource guide: → https://lnkd.in/eYHSjbys ( 750+ students are already using it) This guide will help you with: - DSA, HLD, and LLD for interviews - good resources that I used personally - lots of problems and case studies for DSA and system design

From leaving TCS in Jan 2025… to landing an SDE-1 (L59) offer from Microsoft India in April 2025… This is the story of one of my mentees. (He’s asked me not to tag him, but I’m sharing his full DSA + LeetCode strategy because his approach fixed what most candidates get wrong.) Most students struggle with DSA, not because their logic is weak… but because their approach is broken.  ✅ Step 1: Choose Your Language Based on Speed  Don’t waste time debating Java vs C++ vs Python.  Pick what you’re fastest at when stressed.  Tip: If you’re solving string-heavy questions, Python will save time.  ✅ Step 2: Learn Pattern-Wise This was the biggest game-changer. Instead of solving problems randomly, he studied DSA patterns. → Sliding Window → Two Pointers → Hashing → Recursion + DP → Backtracking → Binary Search on Answers → Monotonic Stack / Queue Every new question became easier to recognize, not just solve. 👉 Here’s my pattern-based learning guide he followed: https://bit.ly/3SmlAzr More on learning DSA pattern-wise here: https://lnkd.in/dkW_CkH5  ✅ Step 3: Get Solid on Time + Space You’re expected to:  Estimate time/space complexity fast  Start with brute force, then optimize  Know tradeoffs (code clarity vs performance) 📌 Before interviews, revise:  Time/space of all core data structures  Big-O notations (keep a printed cheat sheet)  ✅ Step 4: Master the Fundamentals First Don’t rush to DP or Graphs if your basics aren’t solid. He spent his first 4 weeks on: — Arrays — LinkedLists — HashMaps — Stack/Queue operations — Custom implementations like LRU Cache, HashMap 📌 These showed up in his interviews at Microsoft.  ✅ Step 5: Use a Clear, Ordered Roadmap His DSA roadmap looked like this: 1. Arrays, LinkedLists, HashMaps 2. Searching + Sorting 3. Trees (Pre, In, Post order) 4. Graphs, Heaps, Backtracking 5. Recursion 6. DP, Tries, Union-Find He didn’t jump between 10s of DSA sheets out there  ✅ Step 6: Practice With Depth — 10 problems done deeply >> 50 done shallowly — Always ask: “What pattern does this question follow?” Examples:  Max sum of subarray? → Sliding Window  Repeated sub-problems? → Try Recursion → then DP  Multiple paths? → Backtracking  ✅ Step 7: Interview Like a Problem Solver — Start with brute force — Explain your thinking out loud — Clarify the question before writing code — Know your edge cases (nulls, empty inputs, one element) Your goal isn’t to become a LeetCode machine. It’s to become the person who knows how to think, debug, and deliver when it matters. And that’s what this offer from Microsoft proved.

🚀 𝗟𝗲𝗲𝘁𝗖𝗼𝗱𝗲 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝗜 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗳𝗼𝗿 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 Over time, I’ve noticed that most problems follow certain patterns. Identifying the right pattern early makes solving problems much easier. Here are the ones I focus on the most: ✅ 𝗜𝗳 𝘁𝗵𝗲 𝗶𝗻𝗽𝘂𝘁 𝗮𝗿𝗿𝗮𝘆 𝗶𝘀 𝘀𝗼𝗿𝘁𝗲𝗱, 𝘁𝗵𝗲𝗻: Binary search (O(log N) for efficient searching) Two pointers (Optimizing sum/pair problems) ✅ 𝗜𝗳 𝗮𝘀𝗸𝗲𝗱 𝗳𝗼𝗿 𝗮𝗹𝗹 𝗽𝗲𝗿𝗺𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝘀/𝘀𝘂𝗯𝘀𝗲𝘁𝘀, 𝘁𝗵𝗲𝗻: Backtracking (Explore all possible solutions) ✅ 𝗜𝗳 𝗴𝗶𝘃𝗲𝗻 𝗮 𝘁𝗿𝗲𝗲, 𝘁𝗵𝗲𝗻: DFS (Depth-first for deep traversal) BFS (Level-order traversal) ✅ 𝗜𝗳 𝗴𝗶𝘃𝗲𝗻 𝗮 𝗴𝗿𝗮𝗽𝗵, 𝘁𝗵𝗲𝗻: DFS (Finding connected components, cycles) BFS (Shortest path, traversals) ✅ 𝗜𝗳 𝗴𝗶𝘃𝗲𝗻 𝗮 𝗹𝗶𝗻𝗸𝗲𝗱 𝗹𝗶𝘀𝘁, 𝘁𝗵𝗲𝗻: Two pointers (Fast & slow for cycle detection, middle node, etc.) ✅ 𝗜𝗳 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 𝗶𝘀 𝗯𝗮𝗻𝗻𝗲𝗱, 𝘁𝗵𝗲𝗻: Stack (Simulate recursion iteratively) ✅ 𝗜𝗳 𝗺𝘂𝘀𝘁 𝘀𝗼𝗹𝘃𝗲 𝗶𝗻-𝗽𝗹𝗮𝗰𝗲, 𝘁𝗵𝗲𝗻: Swap corresponding values (For sorting or reordering) Store multiple values in the same pointer (Memory optimization) ✅ 𝗜𝗳 𝗮𝘀𝗸𝗲𝗱 𝗳𝗼𝗿 𝗺𝗮𝘅𝗶𝗺𝘂𝗺/𝗺𝗶𝗻𝗶𝗺𝘂𝗺 𝘀𝘂𝗯𝗮𝗿𝗿𝗮𝘆/𝘀𝘂𝗯𝘀𝗲𝘁/𝗼𝗽𝘁𝗶𝗼𝗻𝘀, 𝘁𝗵𝗲𝗻: Dynamic Programming (DP) (Break into overlapping subproblems) ✅ 𝗜𝗳 𝗮𝘀𝗸𝗲𝗱 𝗳𝗼𝗿 𝘁𝗼𝗽/𝗹𝗲𝗮𝘀𝘁 𝗞 𝗶𝘁𝗲𝗺𝘀, 𝘁𝗵𝗲𝗻: Heap (Efficient priority-based extraction) QuickSelect (Optimized selection of Kth smallest/largest) ✅ 𝗜𝗳 𝗮𝘀𝗸𝗲𝗱 𝗳𝗼𝗿 𝗰𝗼𝗺𝗺𝗼𝗻 𝘀𝘁𝗿𝗶𝗻𝗴𝘀, 𝘁𝗵𝗲𝗻: Map (HashMap) (Quick lookup & frequency counting) Trie (Efficient prefix-based searching) ✅ 𝗘𝗹𝘀𝗲: Map/Set (O(1) lookup, O(N) space) Sort input (O(N log N) time, O(1) space) These patterns help break down complex problems and quickly guide me toward an optimal solution. 🚀 💬 Which pattern do you find most useful in interviews? Let’s discuss! #LeetCode #DSA #JobSearch #CodingInterview #FAANG #MAANG #Amazon #Meta #Google #Microsoft #Netflix #Apple #Blind75 #Grind75 #TechInterview #SoftwareEngineering #Algorithms #DataStructures #InterviewPreparation #ProblemSolving #CrackingTheCodingInterview #Careers #SystemDesign #CompetitiveProgramming #FullStackDeveloper #DevCommunity #CodeNewbie #TechCareers #JobSearch #Python #Java #CodingLife #TechIndustry

There are over 3500+ questions on Leetcode and many people are not able to see how DSA patterns keep overlapping even after solving 200-300+ problems. With this pattern recognition cheatsheet you will be able to solve more than 80% of the problems: Think of it as: 1. Identify input type 2. Ask 2 to 3 questions 3. Land on a small set of likely approaches ● Arrays / Strings - Ask first: is it sorted or can I sort it cheaply. - Sorted → Binary Search, Two Pointers, Prefix Sums. - Not sorted → look at intent of the question. ➸ Optimization (max, min, count ways, min cost) - Choices depend on previous choices → Dynamic Programming. - Choices mostly independent with a clear local rule → Greedy, but be ready to justify. ➸Feasibility or existence questions - “Can we do this”, “Is there a solution” → Backtracking, DFS with pruning, or Binary Search on the answer. ➸ String heavy problems - Prefix or suffix logic → Trie, prefix function, rolling hash. - Complex edits, parentheses, next greater element → Stack or Monotonic Stack, sometimes Deque. ➸ Frequent lookups, duplicates, uniqueness - Use Hash Map, Hash Set, or counting array. ➸ Window that grows and shrinks - “Longest subarray”, “smallest substring that” → Sliding Window with Two Pointers, Deque, or a counting map. ➸ Frequent min or max with updates - Use Heap or Monotonic Queue. - Many range queries on big arrays → Segment Tree or Fenwick Tree. ● Graphs - First clarify: directed or undirected, weighted or unweighted, how input is given. ➸ Pathfinding and traversals - Shortest path or fewest steps, unweighted → BFS. - Weighted positive edges → Dijkstra. - Explore all nodes, count components, basic connectivity → DFS, BFS, or Union Find. ➸ Order and dependencies - Course schedule, build order, prerequisites → Topological sort with DFS or Kahn algorithm. - Cycle detection directed → DFS with visited and recursion stack. - Cycle detection undirected → DFS or Union Find. ➸ Global optimisation on graph - Connect all nodes with minimum cost → Minimum Spanning Tree, Kruskal or Prim. - Critical links, bridges, articulation points → Tarjan style algorithms. ● Trees (often binary trees) ➸ Traversals and depths - Level wise questions, distance from root, LCA via parent depth → BFS or DFS with depth. - Combine results from children, like height, path sum, balanced or not → Postorder DFS. ➸ Ordering or special properties - Binary Search Tree hints → Use BST property, inorder, or binary search style traversal. - Many range queries or updates on an array or tree like structure → Segment Tree or Fenwick Tree. ● Linked Lists ➸ Cycle detection - Use fast and slow pointers. ➸ Reversals and structural edits - Reverse list or sublist → Track prev, curr, next. - Insert or delete near head → Use a dummy node to simplify edge cases. ➸ Position based tasks - Find middle, kth from end, intersection → Fast and slow pointers, or length difference trick.

The Right Way to Solve a DSA Problem! I’ve been solving at least one DSA problem on LeetCode almost every day for more than a year... hardly a day goes by when I don’t. And during this time, I realized there’s one common mistake that almost everyone (including me) makes. You start solving a problem. You get stuck. You check the first hint... then the second... then the discussion section. Still can’t figure it out. Finally, you open the solution and boom, it looks so simple. You copy it, submit it, feel great for a moment… and move on. But here’s the problem a month later, you see the same question again and get stuck in the exact same place. You vaguely remember the approach but can’t recall the logic. You open the solution again, try to memorize it again… and the same cycle repeats. Welcome to the DSA Trap... where you think you understood the problem, but can’t solve it on your own. 💡 How to Break Out of it! Start by reading the problem statement properly... understand what’s being asked and what the expected output is. Then, give it time. Think through multiple approaches and always begin with the brute force method. It builds confidence and ensures you’ve understood the problem correctly. Write pseudocode before you code. Pseudocode helps you visualize the logic and exposes the pattern behind the solution. If you still can’t solve it, look at others’ solutions, but don’t just memorize. Understand why the solution works. If it’s still unclear, watch a tutorial (I personally recommend this youtube channel @codestorywithMIK). After you understand the concept, immediately solve 2-3 similar problems. This is how you lock the pattern into your brain. One more practical tip: keep an Excel/Notion sheet or a notebook of problems you couldn’t solve on the first try. Revisit it weekly. Once you can solve a problem on your own, remove it. Over time, the list shrinks and your confidence grows. ✨ Hope this adds some value to your DSA journey! #DSA #ProblemSolving #Coding #LeetCode #Learning #Consistency #Programming

Stop memorizing Leetcode. Start mastering patterns. If you’ve ever felt like you forgot everything the moment the interview started, you’re not alone. Most candidates grind hundreds of Leetcode questions.But during real interviews, they still blank out. Here’s why: You memorized answers. You didn’t learn patterns. The best coders I know: - Recognize that solving Leetcode is an entirely new skill that needs to be honed, and very different from coding in the real world. - Solve fewer Leetcode problems, but spend more time understanding each one - Keep a running list of patterns: sliding window, backtracking, binary search, etc. - Revisit failed problems weekly until they can explain them out loud Here’s what helped me improve fast: - Neetcode’s Roadmap – structured problem types by pattern - Blind 75 List – fewer, high-yield problems - Codeforces Virtual Contests – for timed practice under pressure You don’t need to solve 1000+ questions. You need to understand why each one works. Day 13 of #30DaysOfCareerGrowth #techinterviews #leetcode #codinginterview #techcareers

I solved 400+ LeetCode problems consistently. Still got stuck in interviews midway. Why? Because I didn’t study patterns, I studied just problems. If you're grinding for tech interviews at FAANG or top startups, don’t just brute-force your way through LeetCode. I wasted months before realizing this truth: every top company tests a repeatable set of patterns. Here’s what helped me actually get better and get tech interviews: ✅ Salesforce = hashmap, heap, string manipulation, and recursion. Expect edge cases and real-world data constraints. I used this company-tagged problem list to spot repeated trends.  ✅ Google = loves recursion and trees. Think: backtracking, permutations, and k-ary structures. This LeetCode list helped me master their common types. ✅ Amazon = sliding windows, greedy, and 2 pointers. They test for speed and optimization. Use this Grokking course to drill patterns like sliding window and merge intervals until they’re second nature. ✅ Meta = graphs and BFS/DFS variants. Trust me, you can’t fake graph intuition. NeetCode’s graph sheet was a game-changer for me. ✅ Uber = dynamic programming, interval scheduling, and graphs. They care about your ability to model real-world systems. Practice problems involving route planning, time optimization, and caching logic. The Lesson I learned here? The ultimate shortcut is knowing which coding patterns to master for which company. Check out my DSA Handbook here: https://lnkd.in/eyu9rBn3 Save this post so you’re not solving random LeetCode problems before your next big interview. Tag a friend who’s deep into the coding interview prep mode. Follow Tharun Kumar Reddy Polu for targeted, real-world strategies to land top tech roles. #LeetCode #FAANG #DSA #TechInterviewTips #SoftwareEngineering #Mentorship

If I had 2 weeks to prep for a DE interview at Amazon, here's exactly how I'd prepare for SQL and Problem solving rounds.... My DMs exploded after the last post about interview mistakes. The question everyone's asking? 'But HOW do I actually prepare?' Honestly, you don't need to solve 500 LeetCode problems. You need to practice <100 problems the right way. Quality practice matters over quantity. Your SQL is probably good enough. Your interview approach needs the work. Here's my playbook: The Reality Check ⏱️ In a Typical Coding rounds at Amazon, you would have 15-20 min for each of SQL and DSA, covering 1-2 questions. Not 2 hours. So why practice with infinite time? I'd time every problem that I am solving. - Leetcode Easy problems: 7-10 minutes - Leetcode Medium problems: 10-15 minutes - Can't solve it? I'd revise the associated concepts → Understand pattern → Revisit the question later My brain needs quick recall, not deep meditation. Fix Mistake 1: Silence Kills Interviews 🗣️ I can't suddenly start narrating my thought process on interview day. I'd make it muscle memory. Every practice problem, I'd say OUT LOUD: - "Looking at the schema, I see..." - "My assumption is..." - "I'm choosing JOIN because..." Yes, I will talk to my monitor in an empty room. This IS the skill. Fix Mistake 2: Multiple Solutions = Superpower 💪 Here's what separates good from great: I'd solve every problem TWO ways minimum. - GROUP BY → then window functions - JOINs → then subqueries - Brute Force → then optimized Why? I've literally asked candidates mid-solution: "Now do it without CTEs." Those who practiced variants pivot smoothly while others Freeze. The Formula That Works 👍 That intern who got hired with imperfect solutions? She: - Timed every problem ⏱️ - Narrated her thinking 🧠 - Stated assumptions clearly 🗣️ - Showed multiple approaches 📚 She didn't practice more. She practiced better. Remember: We're not testing your ability to Google in silence. We're evaluating how you'll work with the team. Practice like you'll perform. Start setting a timer when you are practicing next time... ⏰ #DataEngineering #SQLInterviews #InterviewPrep #Amazon