SQL queries + data transformation
Out loud, in order: clarify, build it, check it, explain it.
Practise SQLLoadingone moment…
Data engineering interview · Finance, Payments & Fintech
SQL + PySpark coding and pipeline-architecture/optimization, with real-time payments scenarios.
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And what its data engineers work with.
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Stages in the order candidates meet them.
5 stages. 3 rounds have reported questions, described below.
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The topics it covers and the questions candidates reported.
2 reported questions. See them below
1 reported question. See them below
2 reported questions. See them below
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By round. Questions marked Expected are written from the company's standards.
SQLMedium confidence
Python / PySparkMedium confidence
Pipeline architectureMedium confidence
Nobody reported these exact questions at Razorpay. They are the questions a loop for each of its top topics is known to ask, so prepare for them as likely, not as confirmed.
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Ranked by how much of the evidence points at each topic.
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Do the first group before the second.
SQL + PySpark
Do first (3)Data pipeline architecture + optimization
Real-time payments design (Spark/Kafka, dedup/idempotency)
Cloud (AWS)
ThenBehavioral/cross-functional
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Why candidates were turned down, as reported.
Weak pipeline design/optimization
Design is named in 27 of 50 company accounts.Shaky PySpark
Spark is named in 25 of 50 company accounts.Cannot reason about real-time/idempotency for payments
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2 reported, 3 composite. Each opens and closes. Composites are labelled.
A recruiter call, a technical round, then an onsite with SQL, PySpark, pipeline design and a real-time scenario.
What to take from it Be ready for a real-time pipeline scenario.
Three rounds: SQL with Spark coding; then SQL, data modeling and Spark basics and internals; then a hiring manager round on project experience and behavior. The candidate called the interview good, with a polite and honest recruiter.
What to take from it Know how Spark works inside, as well as how to use it.
Composite walkthroughs. Built from the company's documented loop, not from one person's account.
This is a composite, not one person's account. It is built from the loop we have on record for Razorpay. Questions reported for this round: SQL queries + data transformation; Window functions, dedup, payments analytics.
What to take from it Practise these questions before you reach this round.
This is a composite, not one person's account. It is built from the loop we have on record for Razorpay. Questions reported for this round: Progressively harder Python/SQL/PySpark problems.
What to take from it Practise these questions before you reach this round.
This is a composite, not one person's account. It is built from the loop we have on record for Razorpay. Questions reported for this round: Design/implement pipelines, optimize data flows; Real-time data processing scenarios (Spark/Kafka).
What to take from it Practise these questions before you reach this round.
Razorpay DE-specific verbatim questions are thin online; verify the loop with your recruiter.
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Their reported questions, one at a time, against a stopwatch.
SQL queries + data transformation
Out loud, in order: clarify, build it, check it, explain it.
Practise SQL10
Pick your level and the weeks you have.
Built from what Razorpay asks, strongest first. For the wider basics at your level, follow the Mid level plan alongside it.
Spark and big data
Read: Spark chaptersDrill: Spark playgroundSay it aloud: Spark questionsFull plan: Ace the Spark round
Cloud and tools
Pipeline and system design
Read: Data pipeline chaptersDrill: Pipeline practiceSay it aloud: Data pipeline questionsFull plan: Ace the pipeline round
Python and coding
Read: Python chaptersDrill: Python practiceSay it aloud: Python questionsFull plan: Ace the Python round
Behavioral and communication
Read: Behavioral storytellingSay it aloud: Behavioral questions
Rehearse the Razorpay loop
Run the question deckThen repeat your weakest topic once more.