Razorpay SDE-1 & Junior Analyst — Hiring Structure, Syllabus & 8-Week Prep Plan 2026
Razorpay hiring focuses on fintech engineering for SDE-1 (DSA, LLD, and payment thinking) and analytical excellence for Junior Analysts (aptitude, SQL, and business scenario handling). This guide provides the full roadmap for both tracks.
SDE-1: 2–3 medium-hard coding problems (75–90 min) + Machine Coding/LLD. Junior Analyst: Written test (aptitude), GD, and scenario-based technical rounds.
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Exam Pattern
SDE-1: 2–3 medium-hard coding problems (75–90 min) + Machine Coding/LLD. Junior Analyst: Written test (aptitude), GD, and scenario-based technical rounds.
| Section | Questions | Time | Type | Difficulty |
|---|---|---|---|---|
| SDE-1 · Online Assessment | 2–3 problems + MCQs | 75–90 min | DSA, OS, DBMS, OOP | Medium–Hard |
| SDE-1 · DSA Technical Round | 1–2 problems | 45–60 min | Live coding & complexity | Hard |
| SDE-1 · Machine Coding / LLD | 1 project | 60–90 min | Working in-memory system | Hard |
| SDE-1 · System Design discussion | Varies | 45–60 min | Payments, APIs, Reliability | Medium–Hard |
| Junior Analyst · Written Test | Mixed | Timed | Aptitude & Logical Reasoning | Medium |
| Junior Analyst · Technical Interview | Mixed | 45–60 min | Excel, SQL & Analytics | Medium |
| Junior Analyst · Scenario Interview | 1–2 cases | 45–60 min | Client handling & fintech logic | Medium |
Section-Wise Syllabus
Everything that appears in the assessment, grouped by section.
1. SDE-1 — DSA & Systems
Arrays & Strings
- • Prefix sums
- • Difference arrays
- • Two pointers
- • Sliding window
- • Hashing
- • Sorting-based optimisation
- • Coordinate compression
- • Anagrams
- • Palindromes
- • Minimum window
Linked Lists & Stacks
- • Reverse in groups of k
- • Cycle-entry node
- • Clone random-pointer list
- • Min stack
- • Next greater element
- • Largest rectangle in histogram
- • Sliding-window maximum
Trees & Graphs
- • LCA
- • Validate BST
- • Serialize/Deserialize
- • BFS & DFS
- • Cycle detection
- • Dijkstra
- • DSU
- • Strongly connected components
- • Multi-source BFS
Dynamic Programming
- • House robber
- • Coin change
- • 0/1 knapsack
- • Subset sum
- • Grid DP
- • LIS / LCS
- • Edit distance
- • Stock buy-sell
- • Partition/Interval DP
- • Tree DP
System Design (Fintech)
- • Payment gateway
- • UPI transaction service
- • Wallet ledger
- • Refund & Settlement system
- • Fraud-rule engine
- • Idempotent payment APIs
- • Rate limiter
- • Eventual consistency
2. Junior Analyst — Aptitude & Data
Quantitative Aptitude
- • Percentages & Ratios
- • Profit & Loss
- • Time & Work
- • Speed & Distance
- • Probability
- • Data Interpretation
- • Basic Statistics
Logical Reasoning
- • Series & Coding-decoding
- • Syllogisms
- • Blood relations
- • Puzzles
- • Data sufficiency
- • Analytical caselets
SQL & Analytics
- • Window functions (RANK, LAG, LEAD)
- • CTEs & Subqueries
- • Joins (Self, Inner, Left)
- • Conditional aggregation
- • Cohort analysis
- • Duplicate detection
Excel & Fintech
- • VLOOKUP/XLOOKUP
- • Pivot tables
- • Reconciliation reports
- • KYC & Merchant onboarding
- • Chargebacks vs Refunds
- • Risk scoring
Most Asked Topics
Highest-frequency areas across recent test papers.
Idempotent payment APIs
Request keys to prevent duplicate charges during timeouts or retries.
Wallet ledger design
Using append-only transaction records and double-entry accounting for auditability.
LRU Cache O(1)
Frequently asked machine coding problem using Hash map plus Doubly Linked List.
Transaction success investigation
Segmenting drops by bank, payment method, device, and error codes.
Cycle detection in graphs
Crucial for identifying circular dependencies or fraud loops in settlement networks.
Free Resources
Curated practice links per section.
System & Fintech Design
SQL & Analytics
50+ DSA Practice Problems
Solve in order — arrays and strings first, then sorting and recursion.
Arrays & Strings
- Longest substring without repetition
- Minimum window substring
- Maximum subarray sum
- Product of array except self
- Smallest missing positive
- Merge intervals
Lists & Stacks
- Reverse in groups of k
- Detect cycle entry node
- Clone list with random pointers
- Largest rectangle in histogram
- Sliding window maximum
Graphs & DP
- Shortest path in weighted graph
- Cycle detection
- Number of islands
- Edit distance
- Coin change
- Maximum product subarray
Logic & Sorting
- Minimum swaps to sort
- Cycle decomposition
- Three sum
- Find missing and repeating
Previous Year Questions & Patterns
Repeat coding questions with the expected approach.
SDE-1 Technical
- Design an idempotent payment API with duplicate charge prevention.
- Implement a wallet ledger using double-entry accounting principles.
- Design a rate limiter using the Token Bucket algorithm.
- Find the shortest path in a settlement graph (BFS/Dijkstra).
- Explain transaction atomicity (ACID) in the context of a wallet debit/credit.
Junior Analyst Case Studies
- Success rate dropped from 96% to 89% — how do you investigate?
- How would you identify fraudulent transactions based on IP and velocity?
- What is the difference between a refund and a chargeback?
- How would you measure merchant onboarding success and time-to-activation?
- A merchant reports missing settlement records — how do you reconcile?
20+ SQL Query Bank
Write these out by hand — joins and subqueries are asked in both the test and the interview.
Transaction Metrics
Success rate per day
SELECT DATE(transaction_time) AS txn_date,
100.0 * SUM(CASE WHEN status = 'SUCCESS' THEN 1 ELSE 0 END) / COUNT(*) AS success_rate
FROM transactions
GROUP BY 1 ORDER BY 1;Failed txns by merchant
SELECT merchant_id, COUNT(*) AS failed_count
FROM transactions WHERE status = 'FAILED'
GROUP BY 1 ORDER BY 2 DESC;Customer Behaviour
Repeat customers
SELECT user_id FROM transactions
WHERE status = 'SUCCESS'
GROUP BY user_id HAVING COUNT(DISTINCT transaction_id) > 1;Second highest amount
SELECT MAX(amount) FROM transactions
WHERE amount < (SELECT MAX(amount) FROM transactions);DBMS & Core Interview Q&A
Short answers you should be able to say out loud.
What is the purpose of an Idempotency-Key in APIs?
To ensure that performing the same operation multiple times has the same effect as performing it once, preventing duplicate charges.
Explain RANK() vs DENSE_RANK() in SQL.
RANK() leaves gaps in sequence after ties (1, 2, 2, 4), while DENSE_RANK() does not (1, 2, 2, 3).
Why use append-only ledgers for balances?
For full auditability and to avoid race conditions that occur when directly updating a mutable balance column.
What is eventual consistency in payments?
A model where data across distributed nodes (like ledger and history) will eventually match, though they might be temporarily out of sync.
OOPs Concepts + 10 Code Snippets
Theory plus the exact snippets asked in the technical round.
Strategy Pattern
Used to handle multiple payment methods (UPI, Card, NetBanking) with a common interface.
State Machine
Crucial for tracking transaction lifecycles: PENDING -> AUTHENTICATED -> SUCCESS/FAILED.
SOLID: Single Responsibility
Separating payment initiation from notification and settlement logic.
Composition over Inheritance
Building complex payment features by composing smaller, testable service components.
Idempotent Payment Handler
public class PaymentService {
public PaymentResult process(String idempotencyKey, PaymentRequest req) {
if (cache.exists(idempotencyKey)) {
return cache.get(idempotencyKey);
}
// Process transaction atomically
PaymentResult res = db.executeTransaction(() -> { ... });
cache.set(idempotencyKey, res);
return res;
}
}Wallet Transaction Ledger
-- Append-only ledger query
INSERT INTO ledger (account_id, amount, type, txn_id, status)
VALUES (?, ?, 'DEBIT', ?, 'PENDING');
-- Double-entry match
INSERT INTO ledger (account_id, amount, type, txn_id, status)
VALUES (?, ?, 'CREDIT', ?, 'PENDING');Operating System Basics
Scheduling, deadlock and memory management essentials.
Concurrency & Locking
- • Optimistic vs Pessimistic locking for wallet balances
- • Handling race conditions in multi-threaded payment processing
- • Distributed locks (Redis/Zookeeper) for critical sections
Network & Security
- • TLS/SSL for secure transactions
- • Webhooks and callback security
- • HMAC for request verification
- • Handling network timeouts and retries
4-Week Preparation Roadmap
From zero to test-ready in 28 days.
DSA Foundations
- Arrays, Strings, Hashing
- Sliding Window & Two Pointers
Goal: Master core logic required for the Online Assessment.
Advanced DSA & SQL
- Trees, Graphs, Dijkstra
- SQL Window Functions & Joins
Goal: Prepare for live technical rounds and data analysis tasks.
System Design & Fintech
- LLD: Machine Coding practice
- HLD: Payment systems & Idempotency
Goal: Build working in-memory systems and understand payment architecture.
Excel, Case Studies & Mocks
- Excel/Pivot tables for Analysts
- Timed Mock OAs and Culture rounds
Goal: Finalize domain knowledge and improve communication for scenario rounds.
Exam Day Strategy
Score targets and time allocation.
Section targets
- Online Assessment: Aim for 100% test case pass on 2 problems; partial on 3rd.
- Machine Coding: Focus on working code first, then apply SOLID/clean patterns.
- Junior Analyst Written: Prioritize accuracy over speed in Quant; leave no SQL question empty.
Coding time split (50 min)
- 15 min: Problem understanding & edge cases
- 45 min: Core implementation
- 15 min: Dry run & optimization
Interview Process
What follows the online test.
Technical Evaluation
- • Resume Screening
- • Online Assessment (Coding + CS Fundamentals)
- • Technical Interview (DSA Focus)
- • Machine Coding / LLD Interview
Final Rounds
- • System Design Discussion
- • Hiring Manager / Culture Fit
- • HR / Salary Negotiation
Mock Test Plan
Four simulations to run before the real test.
SDE Mock Assessment
- • 1 Medium String problem
- • 1 Hard Graph problem
- • Implement a simple Rate Limiter
Analyst Mock Assessment
- • 30 Aptitude MCQs
- • 5 SQL queries (Joins + Aggregates)
- • 1 Business Case: Investigate revenue drop
Final Checklist
Tick all of these before test day.
Recent Interview Experiences
First-hand write-ups from students who actually sat the Razorpay process.
Be the first to share a Razorpay interview experience.
Frequently Asked Questions
Is System Design expected for SDE-1?
Yes, basics of LLD and specific payment patterns like Idempotency and Ledgers are frequently asked.
What tools do Junior Analysts need?
Strong proficiency in Excel (Pivot, VLOOKUP) and SQL is essential.
How hard is the Razorpay OA?
It is considered competitive, typically requiring medium-to-hard LeetCode level proficiency.
Want the full structured prep for Razorpay?
The Premium Vault covers Aptitude, Core CS, DSA, SQL and HR rounds with module-wise courses and drill sheets.
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Core CS subjects for this pattern
DBMS & SQL Essentials
Normalisation, keys, transactions and the SQL queries asked in written rounds.
OOPs Essentials for Interviews
The four pillars with the exact code snippets interviewers ask you to explain.
Operating System Essentials
Processes, scheduling, deadlock and memory management in interview-ready form.
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