36 practice questions with answers for SQL interviews in Jaipur.
SQL jobs in Jaipur
Jaipur has a growing IT and IT-enabled services market, with delivery centres, SaaS start-ups and back-office analytics teams around Sitapura and Mahindra World City. Many candidates here also apply to remote and hybrid roles with Delhi NCR teams.
Below are 36 questions that match the mix of service, product and domain employers hiring data analyst (sql)s in Jaipur.
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01
Write a query to show each employee with their manager's name.
SELECT e.emp_id,
e.name AS employee,
m.name AS manager
FROM employees e
LEFT JOIN employees m
ON e.manager_id = m.emp_id;
The same table is used twice with different aliases. LEFT JOIN ensures the CEO, who has no manager, still appears with a NULL manager name.
02
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.
03
A query uses SELECT * on a table with 80 columns. Why is that a problem?
SELECT * fetches every column, increasing disk reads, memory, network transfer and application processing. It prevents covering indexes from being used and can break applications when columns are added or reordered. Select only required columns, which lets the optimiser use narrower indexes and makes the intent clear. SELECT * is acceptable only for quick exploration, not production code.
04
What is the difference between a stored procedure and a function?
A function must return a value or table and can be used inside SELECT or WHERE, but in most databases cannot change data or manage transactions. A stored procedure is executed independently, can return multiple result sets or output parameters, can modify data and control transactions. Use functions for reusable calculations and procedures for workflows such as month-end processing.
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.
06
A long report query has eight nested subqueries and nobody can maintain it. How would you refactor it?
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.
07
Why is NOT IN dangerous when the subquery contains NULL?
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?
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.
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.
10
Write an upsert that inserts a row or updates it if it exists.
PostgreSQL:
INSERT INTO inventory (sku, qty)
VALUES ('A100', 10)
ON CONFLICT (sku)
DO UPDATE SET qty = inventory.qty + EXCLUDED.qty;
MySQL:
INSERT INTO inventory (sku, qty) VALUES ('A100', 10)
ON DUPLICATE KEY UPDATE qty = qty + VALUES(qty);
SQL Server and others use MERGE. A unique key on sku is required.
A star schema has a central fact table with measures such as sales amount and foreign keys to denormalised dimension tables like date, product, store and customer. A snowflake schema normalises dimensions further, such as product to category to department. Star schemas are simpler and faster for BI queries, while snowflake schemas save space and reduce redundancy.
12
An interviewer asks how you would find why a query is slow. What steps do you describe?
First reproduce the issue and measure time. Then check the execution plan for scans, expensive sorts, row estimate errors and join types. Look at indexes on filter and join columns, whether predicates are SARGable, and statistics freshness. Check for blocking or locks from other sessions. Change one thing at a time, measure again, and document the improvement.
13
A search on name LIKE '%sharma%' is very slow on a 20 million row table. What can you do?
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.
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.
15
Tell me about a time you had to deliver a report under a tight deadline.
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.
16
Tell me about a time you automated a manual data task with SQL.
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.
17
Compare this month's and last month's sales per product using a full outer join.
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.
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.
19
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.
DDL (Data Definition Language) defines structure: CREATE, ALTER, DROP, TRUNCATE. DML (Data Manipulation Language) changes data: INSERT, UPDATE, DELETE, and SELECT is often grouped here or as DQL. DCL (Data Control Language) manages access: GRANT and REVOKE. TCL (Transaction Control Language) manages transactions: COMMIT, ROLLBACK and SAVEPOINT. Knowing the categories helps explain behaviour such as auto-commit of DDL in some databases.
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.
22
Describe a time you found and fixed a wrong number in a report.
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.
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.
24
After joining orders with payments, revenue doubled. What went wrong?
Some orders have multiple payment rows, such as partial payments or retries, so each order row repeats and SUM(order amount) counts it multiple times. This is join fan-out. Fix it by aggregating payments per order in a subquery or CTE before joining, or summing order amounts from the orders table alone. Always check row counts before and after a join.
25
What is the difference between FULL OUTER JOIN and UNION of LEFT and RIGHT joins?
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.
26
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.
27
What is a window frame and what is the default frame?
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.
28
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.
29
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').
30
What is the difference between putting a condition in ON versus WHERE in a LEFT JOIN?
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.
31
What is GROUP BY and what is the rule for selected columns?
GROUP BY groups rows that share values in specified columns so aggregates can be computed for each group. Every column in SELECT must either be in GROUP BY or inside an aggregate function. SELECT city, COUNT(*) FROM customers GROUP BY city is valid, but adding name without aggregating it is an error in standard SQL, though older MySQL modes allowed it.
32
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.
33
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.
34
What is the difference between clustered and non-clustered indexes?
A clustered index defines the physical order of rows in the table, so there can be only one, and in SQL Server the primary key creates it by default. A non-clustered index is a separate structure with key values and pointers to rows, and a table can have many. Range queries on the clustered key are very fast, while non-clustered indexes suit selective lookups.
They produce multiple grouping levels in one query. ROLLUP(region, city) gives city totals, region subtotals and a grand total. CUBE(region, product) gives all combinations of subtotals. GROUPING SETS lets you list exact combinations, such as (region), (product) and (). The GROUPING function identifies subtotal rows, which is useful for labelling them in reports.
36
A reporting team wants to query the production OLTP database directly. What are the risks and alternatives?
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.
Few big employers listed in Jaipur?
Many Jaipur candidates also apply to teams in Delhi and to remote or hybrid roles. Practise the Delhi set as well.
Companies with large offices in Jaipur include many IT services and product firms. Use their company pages below to practise employer-specific sets.
Are SQL interviews in Jaipur different from other cities?
The questions depend more on the company than the city. Jaipur's mix of employers decides the style: Many candidates here also apply to remote and hybrid roles with Delhi NCR teams
How do I find SQL jobs in Jaipur?
Shortlist companies with Jaipur offices, keep your CV focused on SQL projects, apply on company career pages and job portals with the Jaipur filter, and practise the questions on this page before each interview.