Interview questions
Preparing for a data engineering interview at Swiggy? This page contains 51 real interview questions sourced from verified Swiggy interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Swiggy data engineering interviews typically focus on SQL, Behavioral, and System Design/Architecture. The interview bar skews toward harder problems (23 hard vs. 14 easy), suggesting emphasis on depth and system-level thinking.
Use the difficulty filters above to focus your preparation. For each question, attempt your own answer first, then compare with our expert solution. You can also practice these questions in our AI Mock Interview Coach for real-time feedback.
Describe a scenario where partitioning and bucketing would improve query performance.
How do you handle late-arriving data in Spark Structured Streaming?
What is the small-file problem in Spark, and how do you solve it?
How do you optimize Spark jobs for better performance? Mention at least 5 techniques.
What are decorators in Python, and how do they work?
Explain the difference between args and kwargs in Python.
Explain the trade-offs between batch and real-time data processing. Provide examples of when each is appropriate.
Retrieve the most recent sale_timestamp for each product (Latest Transaction).
Difference between ROW_NUMBER(), RANK(), and DENSE_RANK() with examples.
Difference between where and having clause with examples.
Explain the difference between UNION and UNION ALL.
Implement a query to find the top 5 customers by total sales amount.
What are primary keys and foreign keys? Why are they important?
What is a self-join, and when would you use it?
What is normalization and denormalization? When would you use each?
What is the difference between a clustered and non-clustered index?
What is the difference between a view and a materialized view?
What is the difference between DELETE and TRUNCATE?
Write an SQL query to find duplicate emails in a users table.
How would you implement a sliding window aggregation in Spark Structured Streaming?
Type or paste your answer to any of these questions and our AI Coach scores it, highlights gaps, and rewrites it at FAANG quality. Free to try.
The Data Engineering Interview Answer Vault bundles 750+ reviewed answers into 7 focused PDF volumes — SQL, Spark, Python, System Design, Cloud, Behavioral, and Data Modeling. Study on any device, no subscription required.
800+ hands-on courses — Grokking System Design, Coding Patterns, and AI mock interviews for your DE loop.
Turn any topic or your own notes into an interactive, personalized course in 60 seconds.
The book that gets data engineers through system-design rounds. Essential reading.
Some links below are affiliate links. If you buy through them we may earn a small commission at no extra cost to you — it helps keep DataEngPrep free.