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SQL Interview Questions in Gurgaon

36 practice questions with answers for SQL interviews in Gurgaon.

SQL jobs in Gurgaon

Gurgaon (Gurugram) is home to many multinational, consulting, fintech and consumer-internet offices. Interviews often expect strong business understanding along with technical skills, especially for analytics and product-facing roles.

Below are 36 questions that match the mix of service, product and domain employers hiring data analyst (sql)s in Gurgaon.

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01

What are the common SQL data types?

SQL BasicsEasy
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Common types are INT, BIGINT and SMALLINT for whole numbers, DECIMAL or NUMERIC for exact values like money, FLOAT for approximate values, CHAR for fixed-length and VARCHAR for variable-length text, DATE, TIME, DATETIME or TIMESTAMP for dates, and BOOLEAN where supported. Choosing correct types saves space, improves performance and prevents errors such as storing amounts in FLOAT and getting rounding issues.
02

What is a covering index?

Indexes and PerformanceMedium
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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.
03

Find employees earning more than the company average.

Subqueries and CTEsEasy
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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.
04

What is the difference between COUNT(*), COUNT(column) and COUNT(DISTINCT column)?

Aggregation and GroupingEasy
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COUNT(*) counts all rows including those with NULLs. COUNT(column) counts rows where that column is not NULL. COUNT(DISTINCT column) counts unique non-null values. In a table of 100 orders where 10 have no coupon and 30 distinct coupons were used, COUNT(*) is 100, COUNT(coupon) is 90 and COUNT(DISTINCT coupon) is 30.
05

Are CTEs materialised or inlined?

Subqueries and CTEsMedium
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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.
06

How do you get the top 3 rows in different databases?

SQL BasicsMedium
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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.
07

Describe your SQL project from college or internship.

Window FunctionsEasy
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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.
08

Management wants the percentage of each category in total sales. How do you write it?

Aggregation and GroupingMedium
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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.
09

What is the logical order of execution of a SELECT query?

SQL BasicsEasy
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The logical order is FROM and JOIN, then WHERE, GROUP BY, HAVING, SELECT, DISTINCT, ORDER BY, and finally LIMIT or OFFSET (or TOP/FETCH). This explains why a column alias defined in SELECT cannot be used in WHERE but can be used in ORDER BY in most databases. The optimiser may execute differently physically, but results follow this logical order.
10

What is the difference between putting a condition in ON versus WHERE in a LEFT JOIN?

JoinsMedium
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In a LEFT JOIN, a condition in ON filters the right table before matching, so all left rows are still kept. A condition on the right table in WHERE runs after the join and removes rows where the right side is NULL, effectively turning it into an inner join. To get all customers with only their 2025 orders, put the date condition in ON.
11

What are database statistics and why do they matter?

Indexes and PerformanceMedium
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Statistics describe data distribution in columns, such as row counts, distinct values and histograms. The optimiser uses them to estimate how many rows each step returns and pick join types and indexes. Stale statistics after large data loads lead to bad plans, such as nested loops over millions of rows. Update them with ANALYZE in PostgreSQL or UPDATE STATISTICS in SQL Server.
12

Can you use window functions with aggregate functions in the same query?

Window FunctionsMedium
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Yes. Window functions are evaluated after GROUP BY, so they can operate on aggregated values. For example, SELECT region, SUM(sales) AS s, RANK() OVER (ORDER BY SUM(sales) DESC) AS rnk FROM orders GROUP BY region ranks regions by total sales. The aggregate is computed per group first, and then the window function runs over the grouped rows.
13

What is the difference between FULL OUTER JOIN and UNION of LEFT and RIGHT joins?

JoinsMedium
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A FULL OUTER JOIN returns matched rows plus unmatched rows from both sides in one operation. MySQL does not support it, so it is emulated with a LEFT JOIN UNION a RIGHT JOIN, or LEFT JOIN UNION ALL a RIGHT JOIN filtered to unmatched rows. Using plain UNION removes duplicates but can also remove genuinely repeated rows, so the UNION ALL pattern is safer.
14

A COUNT(DISTINCT) query on a huge events table is very slow. What options do you have?

Aggregation and GroupingMedium
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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.
15

What are window functions in SQL?

Window FunctionsEasy
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Window functions perform calculations across a set of rows related to the current row without collapsing them into one row like GROUP BY. They use the OVER clause with optional PARTITION BY, ORDER BY and a frame. Examples are ROW_NUMBER, RANK, running SUM, LAG and LEAD. You can show each order alongside the customer's total, which GROUP BY alone cannot do.
16

When should you not create an index?

Indexes and PerformanceMedium
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Avoid indexes on small tables where scans are cheap, on columns with very low selectivity such as a boolean flag used alone, on tables with heavy writes and few reads, and duplicates of existing indexes. Every index slows inserts and updates and uses memory and storage. Review unused indexes periodically with database statistics and drop them after checking dependencies.
17

Tell me about a time you had to deliver a report under a tight deadline.

Aggregation and GroupingMedium
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Situation: the sales head needed region-wise quarterly numbers for a client meeting the same afternoon. Task: deliver accurate figures within three hours. Action: I confirmed metric definitions, reused tested queries, wrote one grouped query with ROLLUP for subtotals and cross-checked totals with the finance summary. Result: the report was delivered in two hours, and it later became a scheduled weekly report.
18

A query that ran in 1 second now takes 40 seconds after a data load. What do you check?

Indexes and PerformanceMedium
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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.
19

What are referential actions such as ON DELETE CASCADE?

Database DesignMedium
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Referential actions define what happens to child rows when a parent row is deleted or updated. CASCADE deletes or updates children automatically, SET NULL sets the foreign key to NULL, SET DEFAULT uses the default value, and RESTRICT or NO ACTION blocks the change. CASCADE is convenient for dependent data like order items but risky on important data, because one delete can remove many rows.
20

Calculate month-over-month revenue growth percentage.

Window FunctionsMedium
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WITH m AS ( SELECT DATE_TRUNC('month', order_date) AS month, SUM(amount) AS revenue FROM orders GROUP BY 1 ) SELECT month, revenue, ROUND(100.0 * (revenue - LAG(revenue) OVER (ORDER BY month)) / NULLIF(LAG(revenue) OVER (ORDER BY month), 0), 2) AS mom_pct FROM m ORDER BY month; NULLIF avoids division by zero.
21

What is the CASE expression and where can it be used?

SQL BasicsMedium
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CASE adds conditional logic in SQL, returning a value based on conditions: CASE WHEN marks >= 60 THEN 'First' WHEN marks >= 45 THEN 'Second' ELSE 'Fail' END. It can be used in SELECT, WHERE, ORDER BY, GROUP BY and inside aggregates, for example SUM(CASE WHEN status = 'Paid' THEN amount ELSE 0 END) to pivot data. Conditions are checked in order and the first true one wins.
22

A long report query has eight nested subqueries and nobody can maintain it. How would you refactor it?

Subqueries and CTEsHard
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Break it into CTEs with meaningful names, each producing one business step such as active customers, order totals and returns. Remove repeated logic, standardise filters, and add comments on business rules. Test each step's row count against the original output. If parts are reused across reports, move them into views. Finally compare results and execution plans to ensure nothing changed.
23

A reporting team wants to query the production OLTP database directly. What are the risks and alternatives?

Database DesignMedium
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Heavy analytical queries can lock rows, use CPU and slow customer transactions, and normalised schemas make reporting complex. Alternatives are a read replica for reporting, a data warehouse loaded by ETL or CDC with a star schema, or materialised summary tables. Grant read-only access with limits if direct access is unavoidable, and schedule heavy jobs off-peak.
24

Compare this month's and last month's sales per product using a full outer join.

JoinsMedium
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SELECT COALESCE(c.product_id, p.product_id) AS product_id, COALESCE(c.sales, 0) AS this_month, COALESCE(p.sales, 0) AS last_month FROM cur_month c FULL OUTER JOIN prev_month p ON c.product_id = p.product_id; Products sold in only one of the months still appear, with zero for the other month.
25

What are transaction isolation levels?

Transactions and Advanced SQLMedium
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Isolation levels balance consistency and concurrency. Read Uncommitted allows dirty reads. Read Committed, the default in PostgreSQL and SQL Server, prevents dirty reads but allows non-repeatable reads. Repeatable Read, the default in MySQL InnoDB, prevents non-repeatable reads, and InnoDB also prevents most phantoms with gap locks. Serializable prevents all anomalies but reduces concurrency. Choose based on business correctness needs.
26

What is a trigger and when should it be used?

Transactions and Advanced SQLMedium
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A trigger is code that runs automatically before or after INSERT, UPDATE or DELETE on a table. It is used for auditing changes, enforcing complex rules and maintaining derived data. Triggers are hidden from application developers, can slow writes and make debugging hard, especially when they cascade. Use them sparingly, document them well, and prefer constraints or application logic when possible.
27

Find duplicate email addresses in a users table.

Aggregation and GroupingMedium
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SELECT email, COUNT(*) AS cnt FROM users GROUP BY email HAVING COUNT(*) > 1; To see full duplicate rows: SELECT * FROM users WHERE email IN ( SELECT email FROM users GROUP BY email HAVING COUNT(*) > 1 ) ORDER BY email; Normalise case with LOWER(email) if needed.
28

What is a primary key and a foreign key?

Database DesignEasy
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A primary key uniquely identifies each row in a table and cannot be NULL or duplicate, such as student_id. A foreign key is a column in one table that references the primary key of another, such as orders.customer_id referencing customers.customer_id. Foreign keys enforce referential integrity, preventing orders for customers that do not exist.
29

Tell me about a time you set SQL coding standards for a team.

Subqueries and CTEsHard
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Situation: our analytics team of eight wrote queries in very different styles, making reviews slow. Task: create common standards. Action: I drafted guidelines on naming, CTE usage, formatting, comments and anti-patterns, added a linter to the repository, and held a short workshop. Result: review time dropped noticeably, new joiners onboarded faster, and production errors from ambiguous queries reduced.
30

How do databases execute GROUP BY internally?

Aggregation and GroupingHard
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The optimiser uses either hash aggregation, building a hash table keyed by group values, which is fast for unsorted data with enough memory, or stream (sort) aggregation, which needs input sorted by the group keys, often from an index. Large groups that do not fit memory spill to disk. Indexes on grouping columns and pre-filtering reduce the cost.
31

Calculate the time each user spent between consecutive events.

Window FunctionsHard
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SELECT user_id, event_time, event_name, event_time - LAG(event_time) OVER ( PARTITION BY user_id ORDER BY event_time ) AS gap_since_prev FROM events ORDER BY user_id, event_time; Gaps above 30 minutes can start a new session using a SUM of a flag over the same window, a common sessionisation pattern.
32

What is the difference between ROW_NUMBER, RANK and DENSE_RANK?

Window FunctionsEasy
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For salaries 900, 800, 800, 700 ordered descending: ROW_NUMBER gives 1, 2, 3, 4 with unique numbers even for ties; RANK gives 1, 2, 2, 4, skipping after ties; DENSE_RANK gives 1, 2, 2, 3 without gaps. Use ROW_NUMBER for deduplication or picking one row, and DENSE_RANK for Nth highest value questions where ties should share a position.
33

What are constraints in SQL?

Database DesignMedium
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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.
34

How does AVG treat NULL values?

Aggregation and GroupingEasy
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AVG ignores NULLs, dividing the sum of non-null values by the count of non-null values. If three employees have bonuses 1000, 2000 and NULL, AVG(bonus) is 1500, not 1000. If NULL should mean zero, use AVG(COALESCE(bonus, 0)). Interviewers ask this to check whether you understand how missing data changes business metrics.
35

What is a composite key?

Database DesignEasy
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A composite key is a primary key made of two or more columns that together uniquely identify a row. For example, in an enrolments table, student_id and course_id together form the key because a student can join many courses and a course has many students, but each pair appears once. Column order in a composite key matters for index usage.
36

A search on name LIKE '%sharma%' is very slow on a 20 million row table. What can you do?

SQL BasicsMedium
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A leading wildcard cannot use a normal B-tree index, so the database scans the table. Options are full-text indexing, trigram indexes in PostgreSQL, a reversed or computed column if the pattern is a suffix, or a search engine for heavy text search. Also limit the result, filter on other indexed columns first, and check whether users really need contains search.

Companies with offices in Gurgaon (5)

Consulting

Accenture

SQL interview questions

  • 30 questions
  • 4 rounds

Bengaluru, Hyderabad, Pune +2

View questions
Product

Amazon

SQL interview questions

  • 30 questions
  • 5 rounds

Bengaluru, Hyderabad, Chennai +2

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Product

Microsoft

SQL interview questions

  • 30 questions
  • 5 rounds

Hyderabad, Bengaluru, Noida +2

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E-commerce & consumer tech

Zomato

SQL interview questions

  • 30 questions
  • 4 rounds

Gurugram

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Consulting

Deloitte

SQL interview questions

  • 30 questions
  • 4 rounds

Hyderabad, Bengaluru, Mumbai +2

View questions

Frequently asked questions

Which companies hire SQL professionals in Gurgaon?

Companies with large offices in Gurgaon include Accenture, Amazon, Microsoft, Zomato, Deloitte. Use their company pages below to practise employer-specific sets.

Are SQL interviews in Gurgaon different from other cities?

The questions depend more on the company than the city. Gurgaon's mix of employers decides the style: Interviews often expect strong business understanding along with technical skills, especially for analytics and product-facing roles

How do I find SQL jobs in Gurgaon?

Shortlist companies with Gurgaon offices, keep your CV focused on SQL projects, apply on company career pages and job portals with the Gurgaon filter, and practise the questions on this page before each interview.

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