FintechVery High demand

Razorpay Data Engineer Interview Questions 2026

Crack the Razorpay Data Engineer interview with these top 10 questions, expert tips, and a 2-week preparation plan. Average salary: ₹10-20 LPA.

About Razorpay's Analytics Team

Razorpay is a leading B2B payments company with strong data science teams working on fraud detection and merchant analytics.

Average salary: ₹10-20 LPASector: Fintech

Skills Required for Razorpay Data Engineer Interview

Razorpay evaluates candidates on these technical and analytical skills. Ensure you are comfortable with at least 70% of this list before applying.

PythonSQLSparkAirflowAWSdbtKafka

Top 10 Razorpay Data Engineer Interview Questions

1.

Tell me about yourself and why you want to be a Data Engineer at Razorpay.

Hint: Focus on your data experience, relevant projects, and genuine interest in the company's data challenges.

2.

Write a SQL query to find the top 5 customers by revenue in the last 30 days.

Hint: Use SELECT, JOIN, WHERE with date filter, GROUP BY, ORDER BY DESC, and LIMIT 5.

3.

How would you clean a dataset with 20% missing values in a key column?

Hint: Discuss imputation strategies (mean/median/mode), domain-specific defaults, or dropping rows based on business impact.

4.

Describe a complex data analysis project you completed end-to-end.

Hint: Use the STAR method: Situation, Task, Action, Result. Quantify the business impact.

5.

Explain the difference between a LEFT JOIN and INNER JOIN with an example.

Hint: INNER JOIN returns only matching rows from both tables. LEFT JOIN returns all rows from the left table and matched rows from the right.

6.

Write a Python function using Pandas to calculate a 7-day moving average.

Hint: Use df[column].rolling(7).mean() in Pandas. Handle edge cases at the start of the series.

7.

Razorpay has seen a 15% drop in a key metric this week. How do you diagnose the issue?

Hint: Structured approach: Check data quality first, then segment (device, region, channel), compare time periods, correlate with product releases or external events.

8.

Explain the concept of data normalization and when it matters.

Hint: Normalization scales features to a common range, important for distance-based algorithms like KNN or clustering.

9.

How would you build a BI dashboard to track Razorpay's key business metrics?

Hint: Identify KPIs with stakeholders, design the data model, build the transformation layer, create the visualization, and schedule refresh.

10.

Where do you see data analytics heading in the next 3–5 years and how are you preparing?

Hint: Mention AI-augmented analytics, real-time analytics, data mesh, and the growing importance of data literacy across organizations.

How to Prepare for Razorpay Data Engineer Interview in 2 Weeks

Week 1: Technical Foundation

  • Practice 50+ SQL queries covering JOINs, CTEs, window functions, and aggregations
  • Review Python and SQL fundamentals and practice problems
  • Study Razorpay's business model and recent analytics case studies

Week 2: Mock Practice & Company Research

  • Complete 3+ mock case study interviews with business metric analysis
  • Practice communicating your portfolio projects using the STAR format
  • Review Razorpay's recent products, features, and data announcements

Master All the Skills Razorpay Looks For

SkillsetMaster's Data Analytics course covers every skill tested in Razorpay's Data Engineer interviews — SQL, Python, Python, SQL, and real-world case studies.

Start Preparing — ₹1,599

Lifetime access · Interview-ready in 8 weeks · Job support included

Data Engineer Interview at Similar Companies