Myntra

The process, round by round

Reported by candidates and, where we found one, the company itself. Each round shows how well it is reported. Processes change by team, level and year.

1. 1

   Online assessment

   Online assessmentAbout 60 minutes (senior report); about 90 minutes in the guide's reports

   One report

   Timed test on a hosted platform. The senior report had 30 MCQs across web basics, Java and data structures plus one coding question; other reports mention one hard array problem or three problems.

   • MCQ fundamentals
   • data structures
   • array problem solving

   Varies: Format differs by role; an internship report in the guide had three problems and some MCQs.

   What can be asked in a online assessment round

   A timed test on a coding platform, taken alone. Usually two or three coding problems, sometimes with multiple-choice questions on CS basics, aptitude or SQL.

   • Array and string problems that need a hash map, two pointers or a sliding window

     Read the constraints first, because they point to the technique. If n is 100,000, an O(n^2) scan will time out, so look for a hash map, two pointers on a sorted array, or a window that moves forward only. Sketch the brute force, find the repeated work, then remove it. For two-sum style pairs you might say: I store each value's index as I scan, so the complement lookup is O(1) and the whole pass is O(n).

     DSA course →
   • Greedy and sorting problems with a catch in the constraints

     Greedy problems hide behind a sort. Ask what ordering makes the locally best choice safe, then try to argue why swapping two adjacent choices never helps. Interval scheduling is the classic case: sort by end time and take every interval that starts after the last chosen one. Check the catch in the constraints, such as overflow, ties or equal values, and test a tiny case by hand before submitting.

     DSA course →
   • A medium dynamic programming or graph-on-a-grid problem

     Decide whether the problem is a graph walk or a recurrence. On a grid, a shortest path with equal step cost is breadth-first search from the start, with a visited set so each cell is processed once, giving O(rows x cols). For dynamic programming, define the state in one sentence, write the transition, set the base cases, then see if only the previous row is needed to save space.

     DSA course →
   • SQL queries with joins and group by

     Start from the table that holds the thing being counted, join the others on their keys, filter rows with WHERE, group, then filter groups with HAVING. Remember that WHERE runs before grouping and HAVING after. Use LEFT JOIN when rows with no match must still appear, and COUNT of a column rather than star when nulls matter. Example: customers with more than three orders is GROUP BY customer_id HAVING COUNT(*) > 3.

     Databases →
   • Multiple-choice questions on OOP, operating systems, databases and networks

     These reward quick, accurate recall rather than long reasoning, so revise the short list of definitions that recur. Know the difference between a process and a thread, the four ACID properties, what an index trades for faster reads, TCP against UDP, and the four pillars of OOP. Eliminate two wrong options first, then choose. Do not spend more than a minute on any single question, and flag it to return to if time remains.

     Mock interviews →

   Prepare with: Book · Online assessmentDSA course

   2 sources for this round

   • Candidate write-upMyntra Interview Experience for Senior SDE (GeeksforGeeks, undated) ↗
   • Prep guideMyntra interview process round by round (DesignGurus) ↗
2. 2

   Live coding (one or two rounds)

   Data structures and algorithmsAbout 60 minutes each (guide)

   One report

   Interviewer-led DSA problems, with trees appearing often per the guide, which also says interviewers ask for running time and alternative approaches. One senior report has two DS-algo rounds; another has one round of three problems plus a follow-up.

   • trees
   • arrays, pairs and stock problems
   • board and grid path problems
   • complexity analysis
   • alternative approaches

   Varies: Senior (5 years) report had two DSA rounds; campus loops weigh core CS more.

   Practise for this round

   • CodingMaximum Overlapping IntervalsMedium · O(n log n)→
   • CodingFirst Non-Repeating Character in a StreamMedium · O(n)→
   • CodingLongest increasing path in a matrixHard · O(m * n) for an m by n grid→

   • ReportedCount distinct pairs with a given difference Reported in a senior DSA round; also listed in a prep guide.Candidate write-up ↗
   • ReportedBest time to buy and sell a stock for maximum profit Appears in a candidate report and a prep guide's question list.Candidate write-up ↗
   • ReportedMinimum knight moves to reach a target square on a board Follow-up asked which board sizes let the knight visit every square.Candidate write-up ↗
   • ReportedBest-sum path through a grid from top row to bottom and back up Round-trip grid path variant; exact original statement not reproduced.Candidate write-up ↗

   Reported prompts have no written answer yet. Read the linked page for context.

   What can be asked in a data structures and algorithms round

   A live coding round of 45 to 60 minutes with one or two problems. You are judged on how you clarify, reason, code, test and state the complexity, not on the answer alone.

   • Arrays, strings and hashing: pairs, windows, frequency counts, prefix sums

     Name the pattern from the shape of the question. Pairs with a target use a hash map of seen values. A contiguous range with a condition uses a sliding window that grows on the right and shrinks on the left, so each element enters and leaves once, giving O(n). Range sums over many queries use a prefix sum array so each query is O(1) after O(n) setup. Count characters with a fixed-size array or map.

     DSA course →
   • Linked lists, stacks and queues, including design-a-structure problems such as an LRU cache

     For an LRU cache, combine a hash map from key to node with a doubly linked list ordered by recency. Get moves the node to the front, put inserts at the front, and when over capacity you remove the tail node and its map entry. Both operations are O(1), and you say why: the map finds the node, the list reorders it without a scan. For stacks, mention a monotonic stack for next greater element.

     DSA course →
   • Trees and BSTs, graphs (BFS, DFS, topological sort, shortest paths) and grids

     Decide the traversal from what is asked. Level by level or shortest path in an unweighted graph is BFS with a queue. Exploring all paths, components or cycles is DFS. A dependency order is topological sort: Kahn's algorithm repeatedly removes nodes with in-degree zero, and leftover nodes mean a cycle. Weighted shortest path with non-negative edges is Dijkstra with a heap, O((V + E) log V). On a BST, an in-order walk is sorted.

     DSA course →
   • Heaps and top-K, intervals, binary search on the answer

     For the K largest items keep a min-heap of size K: push each element and pop the smallest when the heap exceeds K, so the cost is O(n log K) and memory is O(K). For intervals, sort by start, then merge by comparing the next start with the current end. For binary search on the answer, define a yes or no check that is monotonic, such as can ship within D days, and search the capacity range.

     DSA course →
   • Dynamic programming from one dimension up to knapsack and string DP

     Define the state in a sentence, write the recurrence, fix the base cases, and decide the order of filling. Start with the recursive version with memoisation, then convert to a table. For 0/1 knapsack, dp[w] is the best value at capacity w, and in the one dimensional form you loop capacity downward so each item is used once. For string problems such as edit distance, the state is a pair of prefix lengths.

     DSA course →
   • Follow-ups: optimise space, handle streaming input, make it thread-safe

     Treat follow-ups as a chance to show depth, and answer in the same calm order each time. To save space, ask which previous rows or values the recurrence actually reads and keep only those. For streaming input, say what summary you can keep, such as a heap of size K or a running count. For thread safety, name the shared state, guard it with a lock, and keep the critical section short.

   Prepare with: Book · DSA roundDSA course

   3 sources for this round

   • Candidate write-upMyntra Interview Experience, 5 years, Senior Software Engineer (GeeksforGeeks, undated) ↗
   • Candidate write-upMyntra Interview Experience for Senior SDE (GeeksforGeeks, undated) ↗
   • Prep guideMyntra interview process round by round (DesignGurus) ↗
3. 3

   Machine coding / low-level design

   Machine coding

   One report

   Problem given up front and built as a console program in memory: working code and domain-matching classes that accept new requirements. Spend early minutes on clarifying questions. Mostly reported by senior candidates.

   • object modelling
   • working code
   • extensibility
   • requirement clarification

   Varies: Senior roles; the DesignGurus guide says junior candidates rarely report a design round.

   Practise for this round

   • Machine codingOnline store with direct and instalment paymentsStrategy, Adapter · runnable code→

   • ReportedIn-memory e-commerce back end with admin product upload and buying by payment gateway or instalments within a credit limit Machine coding round; products added by console, file or external API.Candidate write-up ↗

   Reported prompts have no written answer yet. Read the linked page for context.

   What can be asked in a machine coding round

   You build a small working system in your own editor in 60 to 120 minutes, then walk through it. Clean entities, extensibility, a runnable demo and tests matter more than clever algorithms.

   • Parking lot, library or inventory system with several entity types

     Spend the first ten minutes on requirements and entities, not code. For a parking lot you might list Vehicle, Slot, Ticket and Lot, with slot types as an enum and the allocation rule hidden behind an interface so a nearest-slot strategy can be swapped. Keep the code runnable early, write a small demo in main, and add a few tests. Say what you would add with more time, such as pricing rules.

     Whiteboard →
   • Splitwise-style expense sharing, a wallet or a ledger

     The core of expense sharing is a balance ledger: for each pair or each user, store the net amount owed. An expense has a payer, an amount and a split type such as equal, exact or percent, handled by a split strategy per type. Validate that exact splits sum to the total and handle rounding explicitly. To simplify debts, compute each person's net balance and match the largest creditor with the largest debtor.

   • Snake and ladder, tic-tac-toe, chess or another game engine

     Model the board, players, dice or moves, and a game controller that owns the turn loop, with rules kept out of the board class. For tic-tac-toe, keep counters per row, column and both diagonals, so a win check is O(1) per move instead of scanning the grid. For snake and ladder, store jumps in a map from square to destination. Make board size and number of players configurable rather than hard coded.

   • An in-memory cache, key-value store, rate limiter or job scheduler

     Start with the public interface and the invariants. For a rate limiter, a token bucket stores tokens and a last refill time per key, refills lazily on each call and allows the request if a token remains. For an LRU or key-value store, say the data structure and the complexity. For a scheduler, a priority queue ordered by run time with a worker that waits for the earliest job.

   • Elevator, vending machine or ATM as a state machine

     Draw the states and transitions before coding. An elevator is idle, moving up, moving down or doors open, and each event such as a button press or arrival is handled by the current state. A vending machine moves through idle, has money, dispensing and out of stock. Implement it with a state interface or an enum and a transition table, so invalid actions are rejected in one place instead of with scattered if statements.

   • Follow-ups: add a new rule without rewriting, make it concurrent, add persistence

     Show that your design bends without a rewrite. For a new rule, say you add a new class that implements the existing interface and register it, leaving old code unchanged. For concurrency, name the shared state and protect it with a lock per resource, or atomic operations, keeping check-and-update in one critical section. For persistence, put a repository interface in front of storage so an in-memory version can be replaced by a database.

     Mock interviews →

   2 sources for this round

   • Candidate write-upMyntra Interview Experience, 5 years, Senior Software Engineer (GeeksforGeeks, undated) ↗
   • Prep guideWhat to expect in the Myntra system design interview (DesignGurus) ↗
4. 4

   System design / hiring manager

   System design

   One report

   Design rounds in the two senior reports: a nearby-places app with schema, API and a location query plus a user feed (caching, push versus pull), and a notification system on database changes. A guide instead folds design into the hiring-manager conversation about current work, stack and API design choices; one report names a hiring-manager round without details.

   • schema and API design
   • caching and feeds
   • scalability trade-offs
   • project depth

   Varies: A guide, citing public statements by Myntra technology leadership, says seniors are also judged on scalability, reliability, performance and security.

   Practise for this round

   • DesignDesign a review-based feed with caching, push and pull4 chapters · diagrams→

   • ReportedDesign a notification system where users subscribe to topics and are alerted on database inserts or updates Example: new employee alerts one team, salary change alerts another.Candidate write-up ↗
   • ReportedDesign a nearby-places app with schema, APIs and a location query optimised for a dense city Follow-up: partitioning and indexing for geographic lookup.Candidate write-up ↗

   Reported prompts have no written answer yet. Read the linked page for context.

   What can be asked in a system design round

   A 45 to 60 minute discussion of how to build a system at scale: requirements, numbers, APIs, data model, components, bottlenecks and trade-offs.

   • Short links, chat, news feed, notifications, search, rate limiting

     Use one repeatable path: clarify scope and scale, estimate load, define the API, sketch the data model, draw the main components, then probe bottlenecks. For short links, store a mapping from a generated short id to the long url, generate ids with a counter encoded in base 62, cache hot links, and note reads far outnumber writes. For chat, mention persistent connections and a store ordered per conversation.

     System design course →
   • Payments, wallets and ledgers where money must never be lost or doubled

     Money systems put correctness before speed. Use a double-entry ledger where entries are append-only and every transfer writes a debit and an equal credit in one transaction. Protect against doubled charges with an idempotency key stored with the result, so a retry returns the original outcome. For lost updates use a database transaction, and reconcile with the payment provider's records on a schedule.

     System design course →
   • Ride matching, maps and anything with live location

     Split the problem into location ingestion, a geospatial index and matching. Drivers send updates every few seconds to a write-optimised store, often in memory, keyed by a grid cell such as a geohash or S2 cell. To find nearby drivers, query the rider's cell and its neighbours, then rank by distance and estimated time. Say how you handle a stale location and a driver who accepts two rides.

     System design course →
   • File storage and sync, video streaming and content delivery

     For file sync, split files into chunks, hash each chunk and upload only chunks the server lacks, so a small edit transfers a small amount. Keep metadata in a database and chunks in object storage. For video, upload the original, transcode into several resolutions, store segments and serve them through a content delivery network with adaptive bitrate streaming, so the player switches quality as bandwidth changes.

     System design course →
   • Fundamentals: caching, sharding, replication, queues, consistency, failure handling

     Treat each as a tool with a cost. A cache cuts read latency but adds staleness and invalidation. Sharding spreads write load but makes cross-shard queries hard. Replication gives availability and read scale but introduces lag. Queues smooth spikes and decouple services but require idempotent consumers. For failures, name timeouts, retries with backoff and a fallback. State what you give up whenever you choose.

     System design course →
   • Back-of-envelope estimates and what they decide

     Estimates are there to choose a design, so finish each one with a decision. Use round numbers: a day has about 100,000 seconds, so 10 million requests a day is roughly 100 per second on average, with a peak of a few times that. Multiply object size by count for storage, and compare against one machine's capacity. If one database handles the load, say so and avoid sharding.

     Capacity estimation →

   Prepare with: Book · System designSystem design course

   3 sources for this round

   • Candidate write-upMyntra Interview Experience for Senior SDE (GeeksforGeeks, undated) ↗
   • Candidate write-upMyntra Interview Experience, 5 years, Senior Software Engineer (GeeksforGeeks, undated) ↗
   • Prep guideMyntra interview process round by round (DesignGurus) ↗
5. 5

   HR round

   HR and offer

   One report

   One senior report covers the most challenging technical work, a design question on Twitter trending hashtags, reasons for leaving, what makes a good team and behavioural questions; the guide lists strengths and weaknesses and the hardest problem solved.

   • motivation for change
   • project ownership
   • team fit

   Varies: The other senior report does not mention an HR round.

   Practise for this round

   • BookWhat each headline number actually pays youHR & the number→
   • BookWhat band should you expect from each type of company?HR & the number→
   • BookWhat are your salary expectations?HR & the number→

   What can be asked in a hr and offer round

   The closing conversation: motivation, expectations, notice period, compensation and how the offer is structured. Prepared answers and a clear number help here.

   • Current and expected compensation, and how to answer without boxing yourself in

     Be honest and avoid giving a single number too early. Share your current pay only if you are comfortable, and make clear what is fixed and what is variable. For expectations, say you are flexible for the right role, and offer a researched range based on level and market. If pushed, state a figure you can justify. Never state a number you cannot support, because offers are often checked.

     HR and the number chapter →
   • Notice period, joining date and relocation

     Give the facts exactly as they are in your contract. State the notice period, whether early release or a buy-out is truly possible, and the earliest honest joining date. Do not promise a date your employer has not agreed to. For relocation, say whether you can move, how soon, and whether you would need support. Clear, early information helps the recruiter plan and shows you are reliable.

     HR and the number chapter →
   • Why you are leaving and what you are looking for

     Keep it positive and forward looking. Talk about what you want more of, such as larger scale, ownership or a stronger team, rather than criticising your current employer. The listener checks that you will not leave this job for the same reason. Opening line: I have learned a lot in the current role, and I now want to work on problems at a bigger scale.

   • Levels, equity and how the offer is built

     Ask for the structure rather than only the total. Find out the level and title, base salary, bonus and whether it is guaranteed, equity amount, vesting schedule and cliff, joining bonus and any clawback. Compare offers on a yearly total with the same assumptions. If equity is in a private company, ask how it is valued and what happens on leaving. Asking calmly is normal and expected.

     Levels and equity chapter →

   Prepare with: Book · HR & the numberBook · Levels & equity

   2 sources for this round

   • Candidate write-upMyntra Interview Experience, 5 years, Senior Software Engineer (GeeksforGeeks, undated) ↗
   • Prep guideMyntra interview process round by round (DesignGurus) ↗

What we could not verify. Neither GeeksforGeeks Myntra page shows an interview date (pages carry only update dates), so both may predate 2022 and no source is confirmed 2022 or later; that is why nothing is graded A. DesignGurus pages are undated aggregators and not independent of the candidate reports. LeetCode, Glassdoor and Naukri Code360 returned 403, so recent (2024-2026) SDE-1/2 reports and a frontend report are not citable. No SDE-2 vs SDE-3 split, no hiring-manager duration, and no GitHub company list found. Rate limiter, parking lot and bus reservation prompts appear only in the prep guide and were left out.