Razorpay Data Analyst Interview Questions 2026: SQL, Cases & Solutions

Cracking a Data Analyst or Business Intelligence role at Razorpay requires more than memorizing basic SQL syntax. As one of the premier employers in the Fintech & Payments Infrastructure space, Razorpay's interview loops are designed to test your ability to translate ambiguous business problems into rigorous, optimized queries and actionable product insights.

In this comprehensive 2026 preparation guide, we break down the 4-stage interview process, explore core SQL problem patterns with working PostgreSQL solutions, analyze key product metrics, and review verified compensation benchmarks.

The Razorpay Data Analyst Interview Process (4 Rounds)

Razorpay structures its analytics hiring loop into four distinct stages:

Round 1: Online SQL & Analytical Assessment (60 Mins)

3 SQL challenges on financial transactions: calculating rolling payment success rates, merchant volume aggregations, and refund reconciliation.

Round 2: Technical Machine Coding & Query Optimization (60 Mins)

Live problem-solving on high-throughput payment tables, indexing strategies for time-series payment logs, and CTE refactoring.

Round 3: Product Sense & Fintech Metrics (45 Mins)

Evaluating payment drop-offs across payment methods (UPI vs Cards vs NetBanking), diagnosing bank downtime vs gateway failure, and merchant cohort LTV.

Round 4: Culture Fit & Director Round (45 Mins)

Analytical ownership, data integrity in financial reporting, and cultural alignment with Razorpay's high-ownership culture.

Top Razorpay SQL Interview Problems & Solutions

Here are realistic SQL problems reflecting the exact domain shapes tested in Razorpay technical rounds:

Problem 1: Payment Gateway Success Rate (PSR) by Bank & Method

Business Scenario:
Razorpay needs to monitor the Payment Success Rate (PSR) for UPI transactions across top issuing banks (HDFC, SBI, ICICI) and identify bank outages where success rate drops below 75%.

Table Schema:

payments(payment_id, merchant_id, bank_code, payment_method, status, created_at)

Optimal SQL Solution (PostgreSQL):

SELECT 
    bank_code,
    COUNT(*) AS total_attempts,
    SUM(CASE WHEN status = 'captured' THEN 1 ELSE 0 END) AS successful_payments,
    ROUND(
        (SUM(CASE WHEN status = 'captured' THEN 1 ELSE 0 END)::numeric / COUNT(*)) * 100, 
        2
    ) AS payment_success_rate
FROM payments
WHERE payment_method = 'upi'
  AND created_at >= NOW() - INTERVAL '1 hour'
GROUP BY bank_code
HAVING COUNT(*) >= 100
   AND (SUM(CASE WHEN status = 'captured' THEN 1 ELSE 0 END)::numeric / COUNT(*)) * 100 < 75.0
ORDER BY payment_success_rate ASC;

Step-by-Step Logic Breakdown:
Calculates real-time Payment Success Rate across banks with conditional aggregation and identifies live bank gateway degradation.

[!TIP] Test your solution in Topfolio's SQL sandbox: Write and run real SQL queries against this exact schema with instant PostgreSQL grading.
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Key Product Metrics & Case Studies at Razorpay

In the product sense round, interviewers will ask you to define metrics and diagnose anomalies. Be prepared for questions such as:

1. North Star Metric Definition: What is the primary North Star metric for Razorpay's core business vertical, and what are 2 counter-metrics to ensure quality is not sacrificed for growth?
2. Funnel Drop-Off Diagnosis: "Conversion dropped by 8% week-over-week in Bengaluru. How would you structure your diagnostic investigation?"
3. A/B Experiment Design: How would you design an experiment to test a new recommendation algorithm without cannibalizing organic merchant search?

2026 Razorpay Data Analyst Salary Bands (India)

Based on verified market submissions, here is how compensation is structured at Razorpay:

For a detailed breakdown of how Razorpay compares to IT Services, GCCs, and Tier-1 tech firms, see our comprehensive Data Analyst Salary Guide 2026 and the India Data Roles Salary Progression Guide.