Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Swiggy hiring for SQL roles
Swiggy is an Indian on-demand delivery platform offering food delivery, Instamart quick commerce and Dineout. Its technology and analytics teams work on delivery time prediction, partner allocation, pricing and customer experience. It hires for software engineers, SDETs, business analysts, data analysts and data scientists. Analysts frequently work closely with operations teams.
For SQL roles, this Swiggy practice set focuses most on Aggregation and Grouping (7), Subqueries and CTEs (5), Transactions and Advanced SQL (4), Database Design (3). It has 2 easy, 23 medium, 5 hard questions, so you can start easy and work up to the harder ones.
Company type
E-commerce & consumer tech
Headquarters
Bengaluru, India
Main India offices
Bengaluru, Hyderabad
Swiggy SQL interview process
Online assessment (coding or SQL)
Technical or case round
Hiring manager round
HR round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
Solved for SwiggyStart practicing
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It depends on the database. SQL Server and MySQL usually inline CTEs like subqueries. PostgreSQL before version 12 always materialised CTEs, which could hurt performance; since version 12 non-recursive CTEs referenced once are inlined, and you can force behaviour with MATERIALIZED or NOT MATERIALIZED. Referencing a heavy CTE many times may cause repeated work, so check the plan.
Constraints enforce rules on data: PRIMARY KEY for unique row identity, FOREIGN KEY for valid references, UNIQUE for no duplicates, NOT NULL for required values, CHECK for conditions like age >= 18, and DEFAULT for automatic values. They protect data quality at the database level, so bad data is rejected even if an application has a bug.
03
You need customers who bought both product A and product B. How would you write it?
Group by customer and count distinct matching products: SELECT customer_id FROM order_items WHERE product_id IN ('A', 'B') GROUP BY customer_id HAVING COUNT(DISTINCT product_id) = 2. Alternatively use INTERSECT of two queries, or two EXISTS conditions. The HAVING approach is concise, scans the table once and is easy to extend to three or more products.
04
Describe your SQL project from college or internship.
Situation: during my internship the team tracked student attendance in spreadsheets. Task: build a database and reports. Action: I designed tables for students, courses and attendance, loaded data, and wrote queries with joins, group by and window functions to show monthly attendance and low-attendance alerts. Result: faculty got a weekly report automatically, and I learned how real data quality issues affect queries.
05
A join between two large tables takes minutes. How would you speed it up?
Check the execution plan for scans, join type and row estimates. Ensure join keys have indexes and matching data types, because implicit conversion blocks index use. Filter both sides early, select only needed columns, update statistics, and avoid functions on join columns. For very large data, consider partitioning, pre-aggregated tables, or batch processing outside peak hours.
A recursive CTE has an anchor member that returns the starting rows and a recursive member that references the CTE itself, joined with UNION ALL. The database repeats the recursive part using the previous iteration's rows until no new rows appear. It is used for hierarchies like org charts, bill of materials and generating sequences. Add a depth limit to prevent infinite loops on cyclic data.
07
Produce region subtotals and a grand total in one query.
SELECT COALESCE(region, 'All Regions') AS region,
COALESCE(city, 'Subtotal') AS city,
SUM(sales) AS sales
FROM store_sales
GROUP BY ROLLUP(region, city)
ORDER BY region, city;
In MySQL use GROUP BY region, city WITH ROLLUP. Use GROUPING() to label totals when real NULLs exist.
08
What is a deadlock and how do databases handle it?
A deadlock occurs when two transactions each hold a lock the other needs, so both wait forever. For example, T1 locks account A and wants B, while T2 locks B and wants A. The database detects the cycle and kills one transaction as the victim, rolling it back with an error. Applications should retry the victim and access resources in a consistent order.
09
Two systems store customer IDs differently, one as INT and one as VARCHAR with leading zeros. How do you join them?
Convert consistently, for example CAST(b.cust_code AS INT) = a.customer_id, but understand this prevents index use on b.cust_code and fails on non-numeric values. Better options are a computed or persisted column with the converted value and an index, or a mapping table built during ETL. Also validate unmatched rows to catch formatting issues such as spaces.
10
Management wants the percentage of each category in total sales. How do you write it?
Use a window aggregate over the grouped result: SELECT category, SUM(sales) AS sales, ROUND(100.0 * SUM(sales) / SUM(SUM(sales)) OVER (), 2) AS pct FROM sales GROUP BY category. The inner SUM is per category and the outer SUM over an empty window gives the grand total. Multiplying by 100.0 avoids integer division in some databases.
11
Write a query to pivot order counts by status into columns.
SELECT
customer_id,
SUM(CASE WHEN status = 'Delivered' THEN 1 ELSE 0 END) AS delivered,
SUM(CASE WHEN status = 'Cancelled' THEN 1 ELSE 0 END) AS cancelled,
SUM(CASE WHEN status = 'Returned' THEN 1 ELSE 0 END) AS returned
FROM orders
GROUP BY customer_id;
Conditional aggregation works in every database, unlike vendor-specific PIVOT syntax.
12
Find departments where every employee earns above 40000.
SELECT d.department_id, d.name
FROM departments d
WHERE NOT EXISTS (
SELECT 1 FROM employees e
WHERE e.department_id = d.department_id
AND e.salary <= 40000
)
AND EXISTS (
SELECT 1 FROM employees e WHERE e.department_id = d.department_id
);
Double negation expresses for all; the EXISTS excludes empty departments.
A lateral join, written as JOIN LATERAL in PostgreSQL and MySQL 8 or CROSS APPLY and OUTER APPLY in SQL Server, lets a subquery in FROM reference columns of tables listed before it. It acts like a correlated subquery that can return multiple rows and columns, ideal for top N per group, for example the three latest orders for each customer.
14
How would you design a database for an online food delivery app at a high level?
Core tables are users, addresses, restaurants, menu_items, orders, order_items, payments, delivery_partners and deliveries. Orders reference users, restaurants and addresses, order_items reference orders and menu_items with price at order time, and payments and deliveries reference orders. Add status history tables for tracking and indexes on user_id, restaurant_id and created_at for common queries.
15
A business user needs a dashboard on a complex 6-table join that runs slowly. Would you use a view or a materialised view?
A normal view only simplifies the query; it still runs the full join every time, so performance does not improve. If the data can be a few minutes or hours old, a materialised view or summary table refreshed on schedule gives fast reads. If real-time data is required, tune the underlying query with indexes or build an incrementally maintained table.
16
Find employees earning more than the company average.
SELECT emp_id, name, salary
FROM employees
WHERE salary > (
SELECT AVG(salary) FROM employees
)
ORDER BY salary DESC;
The inner query is a non-correlated scalar subquery that runs once and returns one value used for comparison.
17
Create a simple stored procedure that returns orders for a customer.
MySQL:
DELIMITER //
CREATE PROCEDURE get_orders(IN p_customer INT)
BEGIN
SELECT order_id, order_date, amount
FROM orders
WHERE customer_id = p_customer
ORDER BY order_date DESC;
END //
DELIMITER ;
CALL get_orders(101);
Parameters prevent SQL injection compared with building query strings in code.
18
How do you get the top 3 rows in different databases?
MySQL and PostgreSQL:
SELECT * FROM products ORDER BY price DESC LIMIT 3;
SQL Server:
SELECT TOP 3 * FROM products ORDER BY price DESC;
Standard SQL:
SELECT * FROM products ORDER BY price DESC
FETCH FIRST 3 ROWS ONLY;
Always use ORDER BY, otherwise the top rows are not guaranteed.
19
You need each customer's latest address from a history table. How do you query it?
Use ROW_NUMBER partitioned by customer and ordered by updated date descending, then keep rn = 1: WITH r AS (SELECT *, ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY updated_at DESC) AS rn FROM address_history) SELECT * FROM r WHERE rn = 1. Add a tiebreaker such as id DESC in case two updates share the same timestamp.
20
A COUNT(DISTINCT) query on a huge events table is very slow. What options do you have?
Exact distinct counts need sorting or hashing all values, which is expensive. Options are filtering the date range tightly, pre-aggregating daily distinct users into a summary table, indexing the columns involved, or using approximate functions such as APPROX_COUNT_DISTINCT or HyperLogLog where small error is acceptable. Explain the accuracy trade-off to stakeholders before switching to approximations.
21
Write a query for monthly revenue for the current year.
SELECT EXTRACT(MONTH FROM order_date) AS month,
SUM(amount) AS revenue,
COUNT(DISTINCT customer_id) AS buyers
FROM orders
WHERE order_date >= DATE '2025-01-01'
AND order_date < DATE '2026-01-01'
GROUP BY EXTRACT(MONTH FROM order_date)
ORDER BY month;
A date range in WHERE keeps an index on order_date usable.
22
What is the difference between SUM with CASE and filtering with WHERE?
WHERE removes rows from the entire query, so all aggregates see only filtered data. SUM(CASE WHEN condition THEN amount END) applies the condition to one aggregate only, letting you calculate several conditional totals in one pass, such as paid and refunded amounts per customer. Some databases support the cleaner FILTER clause: SUM(amount) FILTER (WHERE status = 'Paid').
A SARGable (Search ARGument able) predicate lets the optimiser use an index seek. Wrapping an indexed column in a function, such as WHERE YEAR(order_date) = 2025 or WHERE LOWER(email) = 'x', usually prevents index use. Rewrite as WHERE order_date >= '2025-01-01' AND order_date < '2026-01-01'. Leading wildcards and implicit type conversions also make predicates non-SARGable.
FIRST_VALUE returns the first value in the window frame, LAST_VALUE the last, and NTH_VALUE the nth. A common trap is LAST_VALUE with the default frame, which ends at the current row, so it returns the current row's value. Specify ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING to get the true last value of the partition.
25
Your team debates using UUIDs or auto-increment integers as primary keys. What do you advise?
Auto-increment integers are compact, fast to index and naturally ordered, but expose counts and are hard to generate across distributed systems. UUIDs are globally unique and good for distributed inserts and merging data, but larger and random, causing index fragmentation. Time-ordered UUIDs such as UUIDv7 reduce fragmentation. Choose based on scale, distribution and security needs.
26
A query that ran in 1 second now takes 40 seconds after a data load. What do you check?
Compare the current execution plan with the old one. A big data load often makes statistics stale, causing poor row estimates and a different join or scan choice, so update statistics first. Check for index fragmentation, missing indexes after the load, blocking from other sessions, and whether the data volume crossed a threshold. Test again after each change.
A covering index contains all columns a query needs, either as key columns or included columns, so the database answers the query from the index alone without visiting the table. For SELECT order_date, amount FROM orders WHERE customer_id = 5, an index on (customer_id) INCLUDE (order_date, amount) avoids lookups. It speeds reads but increases index size and write cost.
28
Two users book the last seat at the same time and both succeed. How do you fix it?
This is a race condition. Wrap the check and booking in one transaction and lock the seat row with SELECT ... FOR UPDATE so the second transaction waits and then sees it is taken. Alternatively use an atomic update such as UPDATE seats SET booked_by = :user WHERE seat_id = :id AND booked_by IS NULL and check affected rows, plus a unique constraint as a final safety net.
Use string aggregation: STRING_AGG(name, ', ') in PostgreSQL and SQL Server, GROUP_CONCAT(name SEPARATOR ', ') in MySQL, and LISTAGG in some other databases. Most support ordering inside, for example STRING_AGG(name, ', ' ORDER BY name). It is used to list products in an order or skills of an employee in one row, but watch length limits.
30
Average order value looks too low in a report. What could be wrong?
Check the grain: if the query averages order items instead of orders, each line counts separately and the average drops. Joins can also duplicate rows. Verify whether cancelled or zero-value orders are included and how NULL amounts are treated. Compute SUM(amount) / COUNT(DISTINCT order_id) at order level and compare with business definitions before changing the report.
Tips to crack the Swiggy SQL interview
Prepare cases on order delivery time, delivery partner utilisation or Instamart stock-outs, which match Swiggy's core problems.
Practise SQL on order-level data, including retention, repeat rate and funnel conversion calculations.
Use the Swiggy app critically and be ready to suggest improvements with metrics to track their impact.
Keep a one-minute story ready for every project on your CV: problem, your part, tools, result.
Practise the hard questions on this page aloud; Swiggy interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Swiggy SQL interview?
Candidates usually go through 4 stages: Online assessment (coding or SQL); Technical or case round; Hiring manager round; HR round. The exact rounds change with the role, team, location and your experience, so confirm the process with the recruiter.
Which topics should I prepare for the Swiggy SQL interview?
This practice set leans on Aggregation and Grouping (7), Subqueries and CTEs (5), Transactions and Advanced SQL (4), Database Design (3). Revise those first, then practise explaining one or two of your own projects end to end, because most Swiggy interviewers ask you to walk through real work.
Are these the exact questions asked at Swiggy?
No. These are curated practice questions that match the skills and difficulty usually tested in e-commerce & consumer tech interviews like Swiggy's. They are not a leaked or verified list of past questions.
Where does Swiggy hire SQL professionals in India?
Swiggy has large teams in Bengaluru, Hyderabad. Openings and locations change often, so check the Swiggy careers page and filter by city and experience.