Flipkart Interview Questions India 2026: SDE Process, DSA, System Design, Salary

SDE-1 (0–3 years experience):

Round 1: Online Assessment

• 2 coding problems (LeetCode Medium)
• 90 minutes
• Conducted via HackerEarth or HackerRank

Round 2–3: Technical Coding Rounds (each 60 min)

• 2 coding problems per round (LeetCode Medium to Hard)
• Must explain approach before coding, walk through solution after
• Expect follow-ups: 'Can you optimise this further?', 'What if the input is 10× larger?'

Round 4: Data Structures and Problem Solving (60 min)

• 1 harder problem + discussion of multiple approaches and their tradeoffs
• May include a design question at the data structure level ('Design an order history with efficient search')

Round 5: Behavioural + Hiring Manager (45 min)

• STAR-format questions on teamwork, ownership, impact
• Role alignment: 'Which team/product area interests you?'

SDE-2 (3–7 years): Same structure plus:

• Full System Design round (45–60 min)
• More complex coding problems
• Deeper behavioural assessment with focus on cross-team impact

SDE-3 / Senior SDE (7+ years):

• 2 System Design rounds
• Architecture discussion
• Leadership assessment
• Expected to demonstrate influence beyond immediate team

Flipkart's DSA bar is comparable to Amazon SDE-2: LeetCode Medium-Hard is the target. The problems tend to be application-oriented (connected to e-commerce scenarios) rather than pure academic algorithms.

Most-tested topics at Flipkart India:

1. Arrays and Sliding Window: Flipkart frequently asks problems about efficient data processing (streaming inventory data, price history analysis)

1. Trees and BST: Category tree traversal, product hierarchy queries

1. Graphs: Warehouse network optimisation, delivery route problems

1. Priority Queue / Heap: Top K products by sales, flash sale winner selection

1. HashMap / Two Pointers: Cart deduplication, recommendation system queries

Sample Flipkart-flavoured problem: 'Given a list of orders with (orderId, amount, timestamp), find the maximum total amount from orders placed within any 1-hour window.' ```python from collections import deque def max1hrwindow(orders): orders.sort(key=lambda x: x[2]) window = deque() windowsum = 0 maxsum = 0 for orderid, amount, ts in orders: window.append((orderid, amount, ts)) windowsum += amount while window[0][2] < ts - 3600: windowsum -= window.popleft()[1] maxsum = max(maxsum, windowsum) return maxsum ```

What interviewers look for at Flipkart:

• Working code within time limit (Flipkart is stricter on time than some other companies)
• Explicit complexity analysis before and after optimisation
• Handling of edge cases proactively (not just when pointed out)
• Communication: can you explain the tradeoffs of your chosen approach clearly?

Flipkart's system design round is heavily flavoured by e-commerce problems. Having knowledge of the specific engineering challenges of India's e-commerce market is a differentiator.

Common Flipkart system design questions:

• 'Design Flipkart's product search system'
• 'Design a flash sale system for 10M concurrent users at midnight'
• 'Design Flipkart's recommendation engine'
• 'Design a real-time inventory management system'
• 'Design a delivery tracking system'
• 'Design a fraud detection system for payments'

India-specific e-commerce considerations:

COD (Cash on Delivery): ~40–50% of Indian e-commerce orders are COD. A payment and order system must handle the COD flow (order placed → shipped → collected at delivery → reconciled). This is fundamentally different from prepaid-only systems.

Festival sale spikes: Flipkart's Big Billion Days generates 10–20× normal traffic in 24 hours. Any system design should address: pre-warming caches, rate limiting to prevent overselling, queue-based order processing to handle backpressure.

UPI and wallet integration: Beyond cards, orders go through UPI (NPCI limits: ₹1 lakh per transaction, 20 transactions/day per user per UPI handle): a payment system design must account for these constraints.

Tier-2/3 user base: 60%+ of Flipkart's users are from tier-2 and tier-3 cities with intermittent 4G connectivity. A good candidate mentions: aggressive client-side caching, graceful offline degradation, low-bandwidth image variants.

Flipkart's compensation includes Walmart RSUs (Flipkart is a Walmart subsidiary and Walmart stock: NYSE: WMT: is granted to senior Flipkart engineers).

SDE-1 (0–3 years):

• Base: ₹22–38 LPA
• Walmart RSUs: ₹5–15 LPA (for higher offers)
• Joining bonus: ₹2–5 LPA
• Total Year 1: ₹30–55 LPA

SDE-2 (3–7 years):

• Base: ₹35–55 LPA
• Walmart RSUs: ₹15–35 LPA
• Total: ₹50–90 LPA

SDE-3 (7+ years):

• Total compensation: ₹80–140+ LPA

Flipkart vs Amazon India compensation: At SDE-1 level: Amazon is slightly higher (larger signing bonus). At SDE-2 level: broadly comparable. At SDE-3 and above: Amazon is typically higher (larger stock grants).

Flipkart vs Swiggy/Zomato: Flipkart is 30–50% higher total compensation at comparable levels. The engineering prestige is also significantly higher: a Flipkart SDE-2 offer is typically treated as equivalent to an Amazon SDE-2 offer for next-employer purposes.

Engineering culture at Flipkart:

• Scale: Flipkart handles 8–12M orders per day during peak sale events: genuine hyperscale engineering problems
• Autonomy: Flipkart's engineering teams operate with significant product autonomy vs IT services companies
• Internal tools: Flipkart has built significant internal infrastructure (its own A/B testing platform, data platform, ML infrastructure) that provides meaningful engineering depth
• Post-Walmart: internal access to Walmart's global retail technology stack has created additional learning opportunities