Find the 2 most paid employees from each department (CTE + window functions)
Out loud, in order: clarify, build it, check it, explain it.
Practise SQLLoadingone moment…
Data engineering interview · Commerce, Travel & Marketplaces
Three same-day rounds: Python/DSA/SQL (CTE + window), then DE depth/PySpark and a problem-solving/managerial close.
01
And what its data engineers work with.
02
Stages in the order candidates meet them.
4 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
2 reported questions. See them below
1 reported question. See them below
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By round. Questions marked Expected are written from the company's standards.
SQLHigh confidence
Python / PySparkMedium confidence
Problem-solving / ManagerialMedium confidence
Nobody reported these exact questions at Swiggy. 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 (CTE + window, top-N per group, subqueries)
Do first (3)Python (functions, try-except, decorators, multithreading, Pandas)
PySpark for DE depth
Delivery/logistics pipeline design
ThenProblem-solving/managerial stories
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Why candidates were turned down, as reported.
Weak SQL (CTE/window/top-N)
SQL is named in 37 of 50 company accounts.Shaky Python (decorators/multithreading)
Python is named in 13 of 50 company accounts.Thin problem-solving in R3
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1 reported, 4 composite. Each opens and closes. Composites are labelled.
A round on Python, data structures and SQL (a CTE with a window to find the two highest paid per department, subqueries, decorators and multithreading), an ML round, then a problem-solving and manager round. The first-round SQL and Python level applies to data engineers too.
What to take from it Practise CTEs with windows and basic Python depth.
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 Swiggy. Questions reported for this round: Find the 2 most paid employees from each department (CTE + window functions); Subqueries; top-N per group; order/delivery 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 Swiggy. Questions reported for this round: Functions, try-except, loops, decorators, multithreading; Basic Pandas (groupby); PySpark.
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 Swiggy. Questions reported for this round: Real-world team problems (e.g., delivery-time estimation, dynamic filters).
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 Swiggy. Candidates go through 4 stages, in this order: R1 Python/DSA/SQL, then R2 DE deep-dive / ML, then R3 problem-solving + managerial, then Offer.
What to take from it Know the order, so that no stage surprises you.
Retrieved first-hand is the (adjacent) Data Scientist track; the R1 SQL+Python bar applies to DE. All rounds run the same day.
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Their reported questions, one at a time, against a stopwatch.
Find the 2 most paid employees from each department (CTE + window functions)
Out loud, in order: clarify, build it, check it, explain it.
Practise SQL10
Pick your level and the weeks you have.
Built from what Swiggy 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
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 Swiggy loop
Run the question deckThen repeat your weakest topic once more.