Top 100 LeetCode Problems for MAANG Interviews: Frequency-Ranked with Patterns and Solutions India 2025

Most engineers preparing for MAANG interviews in India waste roughly 60% of their prep time solving problems that simply do not appear in actual interview loops. You've already made it to the HR screen at Google. You're building distributed systems daily at your startup. What's missing isn't more grinding — it's a frequency-ranked signal extracted from real 2024–2025 India interview reports. This list covers the top LeetCode problems for MAANG India, ranked by how often they actually appear at Amazon India, Google India, Flipkart, Swiggy, and Razorpay, tagged by pattern, and mapped to companies. By the end of this guide, you'll know exactly which 100 problems to prioritise, in what order, and why — so your next DSA round is a structured performance, not a gamble.

How This List Was Built

Transparency here matters more than any individual problem on the list. A frequency-ranked list is only worth following if you trust the methodology behind it.

This list was compiled from three primary source types. First, structured interview reports submitted on platforms including Glassdoor India, LeetCode Discuss, and Blind between January 2024 and April 2025, specifically filtered for Amazon India, Google India, Flipkart, Swiggy, Razorpay, and Microsoft India. Second, interview debriefs shared by engineers in MAANG interview prep communities on Reddit (r/cscareerquestions, r/leetcode) with explicit mention of the India office or India interviewer. Third, aggregate frequency data from MAANG DSA round failure patterns tracked across 500+ candidate interview cycles in the FutureJobs network over the same period.

Every problem on this list was reported at least three times within that window. Problems appearing only once or twice in isolated reports were excluded — this eliminates noise from unusual or experimental interview formats. The tier structure (Tier 1, 2, 3) reflects raw frequency: Tier 1 problems appeared in more than 15% of all reported interview rounds, Tier 2 in 6–15%, and Tier 3 in 3–5%.

Company tags on each problem reflect which company's interviewers surfaced that problem most frequently. These are primary associations, not exclusives — Two Sum appears at all five companies, but its Tier 1 placement is driven largely by Amazon India's online assessment data. Where a problem appears across three or more companies equally, it is tagged "Multi-MAANG."

One important qualifier: interview question sets rotate. Companies refresh their problem banks, especially post-hiring-freeze cycles. The 2025 post-layoff hiring environment at Amazon and Google India has pushed interviewers toward medium-hard graph and DP problems more than in 2022–2023. This list reflects that shift. Use it as a living signal, not a static checklist.

The 10 Patterns Behind 90% of Interview Questions

The most efficient insight from aggregating 500+ interview reports is this: interviewers don't test random problems — they test your ability to recognise and apply a fixed set of patterns under time pressure. Memorising solutions is fragile. Pattern recognition is transferable.

The 10 patterns below account for approximately 90% of all reported problems across Amazon India, Google India, Flipkart, Swiggy, and Razorpay interview rounds in 2024–2025. The frequency percentage indicates how often problems from that pattern family appeared in total interview reports.

Key takeaway: If you can pattern-match a new problem to one of these 10 families within the first 3 minutes of reading it, you've already cleared the biggest hurdle in any DSA round. The solution structure follows from the pattern. This is exactly why experienced engineers who've built real distributed systems still fail DSA rounds — they haven't built the pattern recognition reflex that translates product experience into interview performance.

To go deeper on patterns, the Dynamic Programming deep dive and the guide on Monotonic Stack and Queue patterns are the two highest-ROI reads from this list if you're preparing for Flipkart or Swiggy specifically.

Tier 1 — Must-Solve: The Top 30 Highest-Frequency Problems

These 30 problems appeared in more than 15% of reported interview rounds individually or as direct pattern variants. If a problem from this tier appears in your interview and you haven't practised it, you've left a solved problem on the table. Prioritise this tier before anything else.

Each entry includes: Problem Name | Pattern | Difficulty | Primary Company Tag.

Arrays and Two Pointers

Sliding Window

Binary Search

Trees and Graphs

Dynamic Programming

Heap and Priority Queue

Backtracking

Direct Answer Block: The most frequently asked LeetCode problem in MAANG India interviews in 2024–2025 is Two Sum — it appeared in over 22% of reported Amazon India online assessment rounds. However, frequency of appearance doesn't mean it's where you should spend the most prep time. Two Sum is the entry gate; interviewers immediately follow it with a medium-hard variant to test depth. Preparing the pattern family (Hash Map + Two Pointer combinations) matters more than memorising the solution.

Tier 2 — High-Value Medium Problems: The Next 40

These 40 problems appeared in 6–15% of reported interview rounds. They are the difference between clearing the DSA round and being rejected at the second problem. Engineers who only prepare Tier 1 consistently report running out of material in 45-minute rounds that include two to three problems.

Arrays and Strings

Linked List

Trees

Graphs

Dynamic Programming

Heap and Design

Key takeaway: Tier 2 is where most engineers fall short. You know Two Sum cold, but can you implement LRU Cache in 20 minutes while explaining your HashMap + DoublyLinkedList design out loud? Amazon interviewers in India specifically look for clean LRU Cache implementations as a proxy for your data structure design instincts — not just your ability to recall an answer.

Array interview questions for product companies and the complete guide to string interview question patterns will cover the full depth needed for items 31–40 in this tier.

Tier 3 — Hard Problems That Actually Appear: The Final 30

This tier requires a critical nuance: not all hard problems are created equal in MAANG India interviews. The 30 below are hard problems that appear repeatedly in senior-level (SDE II and above) and product-focused company rounds. They are not theoretical exercises — each has appeared in at least three documented India interview reports between 2024 and 2025. If you're targeting roles at ₹25–30 LPA, expect at least one Tier 3 problem in your loop.

Advanced DP

Advanced Graphs

Advanced Trees

Backtracking and Combinatorics

Heap and Advanced Design

Sliding Window and String Hard

System-Adjacent Coding Problems

Insider knowledge signal: Google India interviewers in the 2024–2025 cycle have shown a notable uptick in Trie-based hard problems — specifically Design Autocomplete (problem 92 above) and Word Search II (87). This aligns with Google's internal systems emphasis on search infrastructure. If you're targeting Google India specifically, spending 20% of your Tier 3 prep time on Trie problems has disproportionate ROI.

How to Use This List as a Working Engineer

If you're building real systems all day and prepping for MAANG interviews in the evenings, the standard advice — "solve 3 problems a day" — doesn't map to your reality. Here is a schedule that works within the constraints of a full-time product company role and a life outside work.

Phase 1 — Weeks 1 to 6: Tier 1 Mastery (30 problems) Solve 5 Tier 1 problems per week. One problem per weekday evening, 45–60 minutes per session. Focus entirely on pattern recognition — before you look at the solution, write down which pattern family this problem belongs to. After solving, write a 2-line explanation of your approach in plain English. This trains the verbal explanation reflex that MAANG interviews specifically require.

Phase 2 — Weeks 7 to 14: Tier 2 Deep Work (40 problems) Move to 5 problems per week. Introduce timed sessions — solve each problem with a 25-minute hard cap. If you don't complete it in 25 minutes, stop, review the approach, and re-solve the next day from scratch without looking at your notes. Tier 2 is where pattern fluency converts into speed, which is what separates candidates who clear DSA rounds from those who solve the problem correctly but run out of time.

Phase 3 — Weeks 15 to 20: Tier 3 and Mock Interviews (30 problems) Reduce solo problem solving to 3 per week. Spend the remaining prep time on mock interviews — either with peers, or in structured environments. The biggest failure mode for engineers with 5 years of experience is solving hard problems correctly in silence but being unable to articulate their reasoning under the social pressure of a live interview. You need reps with another human watching.

For engineers who can only find 1 hour per day, the structured 1-hour DSA daily plan maps this exact tiered approach into a realistic 6-month schedule.

Direct Answer Block: How many LeetCode problems should a working engineer solve per day to be MAANG-ready in 5 months? The optimal number is 1 problem per weekday, solved completely — including written complexity analysis and a verbal walkthrough. That produces roughly 100 high-quality solved problems over 20 weeks, which matches this list exactly. Solving 3 problems per day at low depth produces worse outcomes than solving 1 problem per day with deliberate practice.

This List vs Blind 75 vs NeetCode 150 — When to Use Each

This is a question that comes up in every structured DSA prep discussion, and the answer depends on where you are in your preparation and which companies you're targeting.

Blind 75 is a curated list of 75 problems created by a Facebook engineer to cover the most essential LeetCode patterns. It is excellent for engineers who are just getting started with structured DSA prep, particularly those transitioning from service companies who need to build confidence across all core pattern families. If you haven't done consistent DSA in 2+ years, Blind 75 is your starting point, not this list.

NeetCode 150 is an extended version of Blind 75 with 75 additional problems that increase pattern coverage and difficulty. NeetCode's video explanations make it particularly strong for visual learners. For engineers at Swiggy, Meesho, or CRED targeting their first MAANG attempt, NeetCode 150 provides good breadth. However, it is not frequency-weighted for MAANG India specifically — it includes problems that are theoretically important but rarely appear in actual India interview reports.

This list (Top 100, frequency-ranked) is the right choice if you meet three conditions: you've already done 50+ LeetCode problems and understand core patterns, you're specifically targeting MAANG India or Indian product company tier (Flipkart, Razorpay, Swiggy), and you want the highest-ROI problems given constrained prep time. This list is not a replacement for Blind 75 if you're starting from scratch — it is what you graduate to once you have the fundamentals.

The right answer to "Is Blind 75 enough for MAANG India?" is: Blind 75 is sufficient to clear online assessments at most product companies. It is not sufficient to clear full interview loops at Amazon India or Google India at SDE II level, where problem depth, verbal explanation quality, and Tier 3 exposure become decisive factors.

For a complete breakdown of where to start if you're new to structured prep, the foundational DSA explainer and the 30-60-90 day DSA plan give you the full entry-point framework.

How DSA & System Design with AI Program Can Help You

You're already building distributed systems at a Series B product company. The gap isn't real-world experience — it's that no one has shown you how to translate that experience into a 45-minute DSA interview under pressure. That is precisely the gap this program is built for.

FutureJobs' DSA & System Design with AI Program covers this exact 100-problem list across a structured 5-month curriculum — 240+ hours of live classes delivered in evening and weekend slots so your job is never at risk during prep. The curriculum is mapped to pattern families, not random grinding: you build pattern recognition across all 10 families before moving to company-specific problem sets, then to live mock interviews with FAANG mentors who have made the exact transition you're targeting.

The mock interview feedback problem is real. Your friends at Amazon and Google are busy. FutureJobs' 1:1 FAANG mentor model gives you consistent access to engineers who interview at these companies — people who can tell you not just whether your solution is correct, but whether your communication, trade-off articulation, and edge-case handling would pass a real interview loop.

On cost: the pay-after-placement model means your effective upfront commitment is ₹4,999 per month during the program, with the remaining 50% due only after you secure a placement. At a ₹25–30 LPA MAANG offer, that structure is financially straightforward. Compare that to Scaler's ₹5 lakh upfront commitment — a significant EMI risk when you already have financial commitments. FutureJobs is structurally different: the program's incentive is aligned with your outcome, not your enrollment. Over 700 engineers enrolled this month in the DSA program, with the cohort specifically filtered for engineers at the SDE II preparation level.

In 2026, some engineers ask whether DSA still matters when GitHub Copilot and ChatGPT-4o can generate code. The answer is yes — and the bar is higher than before. MAANG interviewers are specifically testing whether you can reason about algorithms in real time, not whether you can write boilerplate. The program's Prompt Engineering module teaches you to use AI tools during your prep efficiently, which accelerates your problem-solving pattern recognition — it does not replace it.

Frequently Asked Questions

What is the most frequently asked LeetCode problem in MAANG India interviews?

Two Sum is the most frequently appearing problem in Amazon India online assessments, showing up in over 22% of reported rounds from 2024–2025. However, it is never the decisive problem — interviewers immediately escalate to medium and hard variants. The pattern family (Hash Map combinations, Two Pointer variations) matters far more than the specific problem. Preparing Two Sum alone won't clear any MAANG loop.

Is Blind 75 enough to crack MAANG India interviews in 2025?

Blind 75 is sufficient to pass online assessments and early screening rounds at most Indian product companies. It is not sufficient for full interview loops at Amazon India or Google India at SDE II level. These companies regularly surface Tier 2 and Tier 3 problems — LRU Cache, Merge K Sorted Lists, Word Ladder, Binary Tree Maximum Path Sum — that fall outside Blind 75's scope. Use Blind 75 as a foundation and graduate to this frequency-ranked 100-problem list for complete coverage.

How many LeetCode problems should I solve per day as a working professional?

One problem per day, solved completely and deliberately, is more effective than three problems solved at surface depth. Complete means: working code, complexity analysis (time and space), a verbal explanation you could deliver to an interviewer, and at least one edge case identified. At one problem per weekday, this list takes exactly 20 weeks — a realistic 5-month timeline while maintaining your current role.

Which tier should I start with if I've already done 50+ LeetCode problems?

Start with Tier 1, regardless of your current experience level. Tier 1 problems are high-frequency — appearing in real interviews — and provide the pattern calibration you need before moving to Tier 2 depth. Many engineers with 5 years of experience discover gaps in Tier 1 pattern fluency because they learned patterns ad hoc rather than systematically. Spending 6 weeks on Tier 1 is never wasted time; it is the foundation that makes Tier 2 and Tier 3 solvable under pressure.

Can I prepare for MAANG interviews while working full-time at a product startup?

Yes — and a product startup background is a genuine advantage for the system design rounds that accompany DSA in MAANG loops. The time constraint is real: budget 1 to 1.5 hours per weekday evening and a 3-hour block on one weekend day. That gives you 8–10 hours per week, which maps to the 20-week schedule in this guide. The critical constraint is consistency, not volume. Engineers who attempt 3–4 hours on irregular weekends consistently underperform those who do 1 hour every weekday without exception.

Do I need to have gone to an IIT or NIT to get a MAANG offer in India?

Product companies in India have largely stopped filtering by college tier at the DSA screening stage. Amazon India, Google India, Flipkart, and Swiggy all run open online assessments where your college name is irrelevant — your solution correctness and efficiency are the only signals. The bar at the offer stage is higher than it was in 2022, but it is uniformly about problem-solving quality and communication, not your educational institution.

How does the FutureJobs DSA program differ from Scaler for someone already at a product company?

FutureJobs' curriculum is calibrated for engineers at the SDE II preparation level — Advanced DSA, system design depth, and mock interview loops with FAANG mentors, not introductory content. The structural difference is financial: Scaler charges ₹5 lakh upfront. FutureJobs uses a pay-after-placement model at ₹4,999 per month during the 5-month program, with the remaining 50% due only after your MAANG offer. For an engineer with existing financial commitments, that difference is material. The FutureJobs mentor profiles let you verify the FAANG background of your potential mentor before enrolling.

Final Thoughts

You now have the complete signal: 100 frequency-ranked problems, 10 pattern families that explain 90% of what gets asked, a company-tagged tier structure, a working-professional prep schedule, and a clear comparison to Blind 75 and NeetCode 150. The methodology behind every claim here is transparent — 500+ India interview reports, 2024–2025 data, filtered for the companies where you actually want to work.

The insight that matters most isn't any single problem on this list. It's the pattern recognition principle underneath it: MAANG interviewers are testing whether you can identify the algorithmic structure of a problem within the first few minutes of reading it. That reflex is built through deliberate, pattern-organised practice — not through random volume.

You've already built distributed systems. You've already reached HR screens at Google. The remaining gap is specific and closable: structured pattern practice, timed execution, and verbal walkthrough fluency under live conditions. This list tells you what to practise. A structured program with the right mentors tells you how to practise it in a way that translates to an offer.

The next step is achievable within your current schedule: start with Tier 1, one problem per weekday, pattern-first. That's it. The 5-month path to your MAANG offer begins with the next 45 minutes you have free.