Flipkart Interview Preparation and Recruitment Process


About Flipkart


Flipkart is a leading Indian e-commerce company founded in October 2007 by Sachin Bansal and Binny Bansal, both IIT Delhi alumni and former Amazon employees. Headquartered in Bengaluru, India, and initially incorporated in Singapore (shifted to India in 2025), Flipkart started as an online bookstore but expanded to offer over 80 million products across 80+ categories, including electronics, fashion, home essentials, groceries, and lifestyle products. It competes primarily with Amazon India and Snapdeal, holding a 48% market share in the Indian e-commerce industry as of FY23.

Flipkart Interview Questions


* Founded:
October 2007

* Founders: Sachin Bansal and Binny Bansal (not related)

* Headquarters: Bengaluru, Karnataka, India

* Parent Company: Walmart Inc. (owns ~77% stake since 2018)

* CEO: Kalyan Krishnamurthy (as of 2025)


Key Highlights:


* Founding and Growth: Launched with an initial family investment of INR 4 lakh, Flipkart began in a two-bedroom apartment in Koramangala, Bengaluru. By 2008, it was receiving 100 orders daily. It gained prominence through aggressive discounts and strong customer service.

* Acquisitions: Flipkart acquired WeRead (2010), Mime360 (2011), Chakpak (2011), Letsbuy (2012), Myntra (2014, $280M), Jabong (2016, $70M), and Cleartrip (distress sale). Myntra operates as a standalone fashion subsidiary.

* Market Position: Dominates apparel (via Myntra) and is neck-and-neck with Amazon in electronics and mobile phones. In 2017, it held a 51% share of Indian smartphone shipments.

* Walmart Acquisition: In 2018, Walmart acquired a 77% stake for $16 billion, valuing Flipkart at $24.9 billion after a $1.2 billion equity round in 2020.

* Innovations: Introduced Flipkart Plus (loyalty program), No Cost EMI, debit card EMI, and Flipkart Minutes (10-minute delivery). It also launched Flyte (music store, shut down in 2013) and PayZippy (payment gateway, merged with Ngpay).

* Technology: Uses MySQL for data storage, Memcached for caching, Hadoop for analytics, and operates on a UNIX-Debian system with JVM.

* Subsidiaries: Owns Myntra, PhonePe (digital payments), Ekart (logistics), Cleartrip (travel), Super.money (fintech), and 2GUD (refurbished goods).

* Challenges: Faced losses (e.g., ₹340 crore monthly burn rate), data breaches at Cleartrip (2017, 2022), and regulatory scrutiny for allegedly breaching foreign investment laws.

* Recent Developments: Plans to go public by 2027, potentially valued at $70 billion, and is moving its holding company to India for higher domestic valuations. It launched a research center in Israel post-acquisition of Upstream Commerce.


Flipkart Recruitment Process


Flipkart's recruitment process for Software Development Engineer (SDE) roles is structured to assess candidates' technical skills, problem-solving abilities, and cultural fit. Here's a comprehensive overview:


Flipkart Recruitment Process Overview

The hiring process typically comprises four main stages:

  1. Online Coding Assessment

    • Platform: Usually conducted on HackerRank.

    • Duration: 90–120 minutes.

    • Questions: 2–3 programming problems focusing on data structures and algorithms.

    • Topics: Arrays, Linked Lists, Trees, Graphs, Recursion, Dynamic Programming, and String Manipulation.

  2. Technical Interview 1

    • Format: Live coding session.

    • Focus: Algorithmic problem-solving, code optimization, and understanding of time and space complexity.

    • Skills Assessed: Proficiency in data structures, algorithms, and coding best practices.

  3. Technical Interview 2

    • Format: Discussion-based interview.

    • Focus: System design principles, object-oriented programming concepts, and low-level design problems.

    • Skills Assessed: Ability to design scalable systems, understanding of OOPs, DBMS, and operating systems.

  4. Hiring Manager Round

    • Format: Behavioral and technical discussion.

    • Focus: Assessment of cultural fit, communication skills, and alignment with Flipkart's mission and values.

    • Topics: Past projects, career aspirations, situational judgment, and leadership capabilities.


Eligibility Criteria

  • Education: Bachelor's or Master's degree in Computer Science or related fields (B.Tech, B.E, M.Tech, M.E, MCA).

  • Academic Performance: Minimum of 60% or 6.5 CGPA in 10th, 12th, and graduation.

  • Backlogs: No active backlogs at the time of the interview.

  • Experience: 0–2 years for SDE-1 roles.


Roles Offered

Flipkart primarily recruits for the following positions:

  • Software Development Engineer (SDE)

  • Backend Developer

  • Frontend Developer

  • Full Stack Developer

Candidates are expected to have strong programming and analytical skills, with proficiency in languages like Java, Python, or C++.


Compensation Details (SDE-1)

  • Fixed Pay: ₹18,00,000 per annum.

  • Performance Bonus: ₹1,80,000 per annum.

  • ESOPs: Approximately ₹1,27,000 annually (25% vested each year).

  • Relocation & Joining Benefits: ₹40,000 for relocation reimbursement and ₹40,000 for travel and accommodation.

  • Total CTC: Approximately ₹21–₹22 LPA.


Preparation Tips

  • Data Structures & Algorithms: Focus on mastering arrays, linked lists, trees, graphs, dynamic programming, and recursion.

  • System Design: Understand low-level design principles and object-oriented programming concepts.

  • Mock Interviews: Practice with peers or mentors to simulate interview scenarios.

  • Project Discussion: Be prepared to discuss your academic or internship projects in detail.

  • Behavioral Questions: Reflect on past experiences to answer situational and behavioral questions effectively.

Flipkart Interview Questions :

1 .
How to Reverse a Linked List?

To reverse a linked list, use an iterative or recursive approach.
Iterative Method:

  • Initialize three pointers: prev (null), current (head), and next (null).

  • Traverse the list, updating next to current.next, then reverse the link by setting current.next to prev.

  • Move prev and current forward. Repeat until current is null. The new head is prev.
    Time Complexity: O(n), Space: O(1).
    Recursive Method:

  • Base case: If the node is null or the last node, return it as the new head.

  • Recursively reverse the rest. Set current.next.next to current, and current.next to null.
    Time Complexity: O(n), Space: O(n) (stack).

2 .
Find the Middle Element of a Linked List

Use the two-pointer (Tortoise and Hare) approach:

  • Initialize slow and fast pointers at the head.

  • Move slow by 1 node and fast by 2 nodes in each iteration.

  • When fast reaches the end, slow points to the middle.
    Edge Cases:

  • Even nodes: Return the first or second middle based on requirements.
    Time Complexity: O(n), Space: O(1).
    Example: In 1 -> 2 -> 3 -> 4 -> 5slow stops at 3.

3 .
Implement a Queue Using Stacks

Use two stacks (s1 and s2):
Enqueue: Push elements to s1Time: O(1).
Dequeue:

  • If s2 is empty, transfer all elements from s1 to s2 (reversing order).

  • Pop from s2Amortized Time: O(1) per operation.
    Example:

  • Enqueue 1, 2, 3: s1 = [1, 2, 3].

  • Dequeue: Transfer to s2 = [3, 2, 1], pop 1.
    This approach ensures FIFO order efficiently.

4 .
Check for Balanced Parentheses

Use a stack to track opening brackets:

  • Traverse the string. For (, {, [, push to stack.

  • For closing brackets, check if the stack is empty (unbalanced) or if the top matches.

  • After traversal, the stack must be empty.
    Example{[()]} is balanced. {[}] is not.
    Edge Cases:

  • Empty string: Balanced.

  • Extra closing brackets: Unbalanced.
    Time: O(n), Space: O(n).

5 .
Longest Palindromic Substring

Use expand around center approach:

  • For each character, expand left and right to find the longest odd-length palindrome.

  • Repeat for even-length (centered between two characters).

  • Track the maximum length and its start index.
    Example: For "babad", the longest is "aba" or "bab".
    Time: O(n²), Space: O(1).
    Alternative: Dynamic Programming (table for substring validity) but uses O(n²) space.

6 .
Design a URL Shortening Service

Components:

  • Short URL Generation: Use hash functions (e.g., MD5) or Base62 encoding of a unique ID.

  • Database: Store mappings (shortURL, longURL, expiry).

  • Redirection: HTTP 301/302 redirects.
    Optimizations:

  • Caching: Use Redis for frequent requests.

  • Scalability: Database sharding, load balancers.

  • Collision Handling: Retry on hash collision.
    Example: TinyURL uses Base62 encoding for 7-character short URLs.

7 .
Design an E-commerce Platform

Key Services:

  • User Service: Authentication, profiles.

  • Product Service: Catalog, search (Elasticsearch).

  • Order Service: Transactions, inventory updates.

  • Payment Gateway Integration: Idempotent API for payments.
    Scalability:

  • Microservices: Isolate failures.

  • Database: Sharding (by user/product), read replicas.

  • Caching: Redis for product details.

  • Async Processing: Queues (Kafka) for order processing.
    High Traffic: CDN for images, auto-scaling, rate limiting.

8 .
Explain Database Indexing

Indexes (e.g., B+ trees) speed up queries by reducing disk I/O.
Clustered Index: Determines data storage order (e.g., primary key).
Non-Clustered Index: Separate structure with pointers to data.
Trade-offs:

  • Faster reads vs slower writes (index updates).

  • Use for columns in WHERE, JOIN, ORDER BY.
    Example: Index on users.email speeds up login queries.

9 .
SQL vs NoSQL
SQL:

* Structured, ACID transactions, relational schema.

* Use for complex queries (e.g., banking).

NoSQL:

* Flexible schema, horizontal scaling (e.g., MongoDB, Cassandra).

* Use for unstructured data (e.g., social media).

Choice Depends On: Data structure, scalability needs, consistency vs flexibility.
10 .
Normalization in Databases
Goal: Reduce redundancy via table splitting.
1NF: Atomic values, no repeating groups.
2NF: No partial dependencies (all non-key attributes depend on the full primary key).
3NF: No transitive dependencies.
Example: Split Orders into Orders and Customers to avoid repeating customer data.
11 .
ACID Properties
  • Atomicity: Transactions are all-or-nothing.

  • Consistency: Valid state transitions (e.g., no negative balance).

  • Isolation: Concurrent transactions don’t interfere (via locks/MVCC).

  • Durability: Committed data survives crashes.
    Example: Bank transfers require ACID to prevent errors.

12 .
Deadlock and Prevention

Deadlock: Processes hold resources and wait cyclically.
Conditions: Mutual exclusion, hold and wait, no preemption, circular wait.
Prevention:

  • Resource ordering: Acquire resources in fixed order.

  • Timeouts: Release resources after a period.

  • Deadlock detection: Periodically check for cycles.

13 .
Multithreading vs Multiprocessing
Multithreading:

* Shares memory, lightweight.

* Use for I/O-bound tasks (e.g., web servers).

Multiprocessing:

* Isolated memory, better for CPU-bound tasks.

* Avoids GIL in Python.

Example: Chrome uses processes per tab for stability.
14 .
HashMap vs HashTable
HashMap:

* Not synchronized, allows one null key.

* Faster in single-threaded apps.

HashTable:

* Synchronized (thread-safe), no nulls.

* Prefer ConcurrentHashMap for better concurrency.
15 .
Polymorphism
Runtime (Method Overriding):

* Subclasses override methods (e.g., Animal.speak() for Dog/Cat).

Compile-time (Overloading):

* Same method name, different parameters.

Example: Payment.process() handles credit cards, UPI differently.
16 .
RESTful API
  • Stateless: No client context stored.

  • HTTP Methods: GET (read), POST (create), PUT (update), DELETE.

  • Status Codes: 200 (OK), 201 (Created), 404 (Not Found).
    Best Practices: Versioning (/api/v1), HATEOAS, pagination.

17 .
Handle High Traffic
  • Horizontal Scaling: Add more servers.

  • Caching: CDN for static content, Redis for DB queries.

  • Database: Read replicas, sharding.

  • Async: Queues for non-critical tasks (e.g., emails).

18 .
Load Balancing

Algorithms:

  • Round Robin: Distribute requests sequentially.

  • Least Connections: Send to least busy server.
    Tools: AWS ALB, NGINX.
    Benefits: Redundancy, improved uptime, scalability.

19 .
Microservices Architecture
Benefits:

* Independent deployment, fault isolation.

* Scalability per service.

Challenges: Network latency, distributed logging.

Tools: Docker, Kubernetes, Istio.
20 .
Secure an API
  • HTTPS: Encrypt data in transit.

  • OAuth2/JWT: Token-based authentication.

  • Rate Limiting: Prevent abuse.

  • Input Validation: Sanitize user inputs.