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SQL Interview Questions in Pune

36 practice questions with answers for SQL interviews in Pune.

SQL jobs in Pune

Pune combines IT-services campuses in Hinjewadi and Kharadi with product, automotive and BFSI technology centres. It has a large mid-level job market for data and QA roles, and interviews are often practical and project-based.

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

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01

What is the difference between a correlated and a non-correlated subquery?

Subqueries and CTEsEasy
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A non-correlated subquery runs independently and returns a result once, such as the overall average salary. A correlated subquery references columns from the outer query and logically runs for each outer row, such as comparing each employee's salary with the average of their own department. Correlated subqueries are powerful but may be slow without good indexes, although optimisers often rewrite them as joins.
02

An interviewer asks for the Nth highest salary in a reusable way. How do you answer?

Subqueries and CTEsMedium
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Use DENSE_RANK so ties share a rank: SELECT salary FROM (SELECT salary, DENSE_RANK() OVER (ORDER BY salary DESC) AS r FROM employees) t WHERE r = :n. Alternatively use ORDER BY salary DESC with OFFSET n-1 ROWS FETCH NEXT 1 ROW ONLY on distinct salaries. Mention how ties are handled and that per-department versions add PARTITION BY department_id.
03

Your query WHERE manager_id <> 5 is not returning employees who have no manager. Why?

SQL BasicsMedium
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Employees with no manager have manager_id as NULL, and NULL <> 5 evaluates to unknown, not true, so those rows are excluded. Rewrite it as WHERE manager_id <> 5 OR manager_id IS NULL, or use COALESCE(manager_id, 0) <> 5. This three-valued logic with true, false and unknown causes many subtle bugs in reports and NOT IN subqueries.
04

Two users book the last seat at the same time and both succeed. How do you fix it?

Transactions and Advanced SQLMedium
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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.
05

Find cities with more than 100 customers.

Aggregation and GroupingEasy
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SELECT city, COUNT(*) AS customers FROM customers GROUP BY city HAVING COUNT(*) > 100 ORDER BY customers DESC; HAVING is needed because the condition uses an aggregate. A WHERE clause could still filter rows first, for example only active customers.
06

What do NTILE, PERCENT_RANK and CUME_DIST do?

Window FunctionsMedium
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NTILE(n) splits ordered rows into n roughly equal buckets, useful for quartiles or deciles. PERCENT_RANK returns (rank - 1) / (rows - 1), a relative position between 0 and 1. CUME_DIST returns the fraction of rows with values less than or equal to the current row. They are used for customer segmentation, percentile reports and scoring.
07

Why is NOT IN dangerous when the subquery contains NULL?

Subqueries and CTEsMedium
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If the subquery returns any NULL, value NOT IN (list) becomes unknown for every row, because comparing with NULL is unknown, so the query returns no rows. For example, NOT IN (SELECT manager_id FROM employees) fails when a manager_id is NULL. Use NOT EXISTS or filter out NULLs in the subquery to get correct results.
08

Finance asks for the count of customers whose total spend crossed 1 lakh in each city. How do you write it?

Aggregation and GroupingHard
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Aggregate in two levels. First compute total spend per customer and city in a CTE: SELECT city, customer_id, SUM(amount) AS spend FROM orders GROUP BY city, customer_id. Then in the outer query: SELECT city, COUNT(*) FROM cte WHERE spend > 100000 GROUP BY city. Trying to do it in one GROUP BY by city fails because the threshold applies to each customer, not each city.
09

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.
10

Describe a time you found and fixed a wrong number in a report.

JoinsMedium
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Situation: a monthly dashboard showed 30 percent higher revenue than finance figures. Task: find the cause before the leadership review. Action: I traced the SQL, found a join to the shipments table that duplicated orders with split shipments, rewrote it with a pre-aggregated CTE and reconciled totals with finance. Result: numbers matched exactly and I added a row-count test to the report pipeline.
11

What are surrogate keys and natural keys?

Database DesignMedium
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A natural key is a real-world identifier like PAN number, email or product code. A surrogate key is a system-generated value, usually an integer or UUID, with no business meaning. Surrogate keys are stable, compact and good for joins, while natural keys can change or be long. A common design uses a surrogate primary key plus a unique constraint on the natural key.
12

What is the difference between ROWS and RANGE frames?

Window FunctionsMedium
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ROWS counts physical rows, so 2 PRECEDING means exactly two rows before. RANGE works on values of the ORDER BY column, so rows with the same value are treated together, and value ranges like INTERVAL '7 days' PRECEDING are possible in some databases. With duplicate dates, a RANGE running total jumps for all ties at once, while ROWS increases row by row.
13

How do you prevent SQL injection in applications?

Transactions and Advanced SQLMedium
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Never build SQL by concatenating user input. Use parameterised queries or prepared statements, where input is sent separately from the SQL text, or ORMs that do this automatically. Validate and whitelist inputs such as sort column names, give application users least privilege, and avoid dynamic SQL in procedures unless parameters are bound. Input like ' OR 1=1 -- then cannot change the query logic.
14

What is a window frame and what is the default frame?

Window FunctionsMedium
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A frame defines which rows around the current row are included, such as ROWS BETWEEN 2 PRECEDING AND CURRENT ROW for a 3-row moving average. When ORDER BY is present and no frame is specified, the default is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, which produces a running total but includes all ties of the current value. Without ORDER BY, the frame is the whole partition.
15

Rewrite a nested query using CTEs for readability.

Subqueries and CTEsMedium
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WITH order_totals AS ( SELECT customer_id, SUM(amount) AS total FROM orders GROUP BY customer_id ), ranked AS ( SELECT customer_id, total, NTILE(10) OVER (ORDER BY total DESC) AS decile FROM order_totals ) SELECT * FROM ranked WHERE decile = 1; Each CTE is a named step, making top 10 percent customer logic easy to read.
16

Produce region subtotals and a grand total in one query.

Aggregation and GroupingMedium
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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.
17

What is the difference between a join and a union?

JoinsMedium
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A join combines columns from different tables side by side based on a matching condition, making rows wider. A union stacks results of queries with the same column structure vertically, making the result longer. Use a join to bring customer names next to orders, and a union to combine 2024 and 2025 order tables into one list.
18

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.
19

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.
20

How do you handle a situation where business users dispute your numbers?

Aggregation and GroupingHard
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Situation: a regional manager said my sales report undercounted his region. Task: resolve it with facts. Action: I shared the query logic and definitions, compared a sample of his records with the database, and found his team counted orders on booking date while the report used invoice date. Result: we agreed on invoice date with finance, documented it, and added the definition to the report.
21

How do SQL dialects differ and how do you write portable SQL?

SQL BasicsHard
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Databases differ in row limiting (LIMIT, TOP, FETCH), string concatenation (|| versus + versus CONCAT), date functions, identity columns (AUTO_INCREMENT, IDENTITY, SERIAL), upsert syntax and case sensitivity. For portable SQL, use ANSI features such as CASE, COALESCE, standard joins, window functions and FETCH FIRST where supported, keep vendor-specific logic isolated, and test against each target database.
22

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.
23

A query with a correlated subquery in SELECT runs for every row and is slow. How do you improve it?

Subqueries and CTEsMedium
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Rewrite the correlated scalar subquery as a join to a pre-aggregated derived table or CTE, for example aggregate order counts per customer once and LEFT JOIN it. Alternatively use a window function. Ensure the correlation column is indexed if you keep the subquery. Compare execution plans and timing before and after to confirm the improvement.
24

What is the difference between IN and EXISTS?

Subqueries and CTEsMedium
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IN checks whether a value matches any value in a list or subquery result. EXISTS checks whether a correlated subquery returns at least one row and stops at the first match. Modern optimisers often treat them similarly, but EXISTS is clearer for correlated checks and handles NULLs safely. For large subquery results, EXISTS with an index on the join column is usually efficient.
25

What does DISTINCT do and how is it different from GROUP BY?

SQL BasicsMedium
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DISTINCT removes duplicate rows from the result based on all selected columns. GROUP BY groups rows so you can apply aggregates per group. SELECT DISTINCT city FROM customers and SELECT city FROM customers GROUP BY city give the same output, but GROUP BY is needed when you also want counts or sums. Overusing DISTINCT to hide duplicate join rows is a common mistake.
26

What is the difference between MIN/MAX on numbers and on strings or dates?

Aggregation and GroupingEasy
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MIN and MAX work on any comparable type. On numbers they return smallest and largest values, on dates the earliest and latest, and on strings the first and last in alphabetical order based on collation. MAX(order_date) gives the latest order, and MIN(name) gives the alphabetically first name, which is useful but not a meaningful business metric by itself.
27

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.
28

Calculate a 7-day moving average of daily active users.

Window FunctionsMedium
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SELECT activity_date, dau, ROUND(AVG(dau) OVER ( ORDER BY activity_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW ), 1) AS dau_7d_avg FROM daily_users ORDER BY activity_date; This assumes one row per day; fill missing dates with a calendar table first, or ROWS will span more than seven days.
29

Write a query for monthly revenue for the current year.

Aggregation and GroupingMedium
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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.
30

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.
31

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

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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.
32

Get the latest 3 orders for every customer using a lateral join.

Subqueries and CTEsHard
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SELECT c.customer_id, o.order_id, o.order_date FROM customers c CROSS JOIN LATERAL ( SELECT order_id, order_date FROM orders WHERE orders.customer_id = c.customer_id ORDER BY order_date DESC LIMIT 3 ) o; With an index on (customer_id, order_date), each lookup is fast. SQL Server uses CROSS APPLY with TOP 3.
33

Rewrite a non-SARGable date filter to use an index.

Indexes and PerformanceMedium
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Slow: SELECT * FROM orders WHERE YEAR(order_date) = 2025 AND MONTH(order_date) = 3; Fast: SELECT * FROM orders WHERE order_date >= '2025-03-01' AND order_date < '2025-04-01'; The second form compares the raw column, so an index on order_date can be used with a range seek.
34

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.
35

Tell me about a time you automated a manual data task with SQL.

SQL BasicsMedium
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Situation: the operations team spent four hours every Monday merging Excel files for a weekly report. Task: reduce the effort. Action: I loaded the files into staging tables, wrote SQL with joins and aggregations to produce the report, and scheduled it as a job. Result: the report was ready automatically at 8 AM, saving about 16 hours a month and removing copy-paste errors.
36

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.

Companies with offices in Pune (11)

IT services

TCS

SQL interview questions

  • 30 questions
  • 4 rounds

Mumbai, Chennai, Pune +2

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IT services

Infosys

SQL interview questions

  • 30 questions
  • 4 rounds

Bengaluru, Mysuru, Pune +2

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IT services

Wipro

SQL interview questions

  • 30 questions
  • 4 rounds

Bengaluru, Hyderabad, Pune +2

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Consulting

Accenture

SQL interview questions

  • 30 questions
  • 4 rounds

Bengaluru, Hyderabad, Pune +2

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IT services

Cognizant

SQL interview questions

  • 30 questions
  • 4 rounds

Chennai, Bengaluru, Pune +2

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IT services

Capgemini

SQL interview questions

  • 30 questions
  • 4 rounds

Mumbai, Bengaluru, Pune +2

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IT services

Tech Mahindra

SQL interview questions

  • 30 questions
  • 4 rounds

Pune, Hyderabad, Bengaluru +2

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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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Fintech

PhonePe

SQL interview questions

  • 30 questions
  • 5 rounds

Bengaluru, Pune

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Consulting

Deloitte

SQL interview questions

  • 30 questions
  • 4 rounds

Hyderabad, Bengaluru, Mumbai +2

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Frequently asked questions

Which companies hire SQL professionals in Pune?

Companies with large offices in Pune include TCS, Infosys, Wipro, Accenture, Cognizant, Capgemini, Tech Mahindra, Amazon, Microsoft, PhonePe. Use their company pages below to practise employer-specific sets.

Are SQL interviews in Pune different from other cities?

The questions depend more on the company than the city. Pune's mix of employers decides the style: It has a large mid-level job market for data and QA roles, and interviews are often practical and project-based

How do I find SQL jobs in Pune?

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

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