SQL Interview Questions by Role

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Not all SQL interview questions are one-size-fits-all. Depending on the role you’re applying for – be it a Product Manager, Data Analyst, or Data Engineer – the focus and style of SQL questions can differ. Interviewers tailor questions to assess the SQL proficiency relevant to your role’s responsibilities. Let’s break down what you might expect:

For Product Managers (PMs)

Product Managers are not usually writing complex SQL in their day-to-day work, but they are often expected to be data-driven and comfortable pulling basic metrics. In an interview, PM-oriented SQL questions tend to be high-level, focusing on interpreting data or knowing what to query for, rather than intricate query syntax. You might encounter questions like:

• “What query would you write to find the number of user sign-ups per month?” – expecting something like SELECT MONTH(signup_date), COUNT(*) FROM Users GROUP BY 1;.
• “How can you find how many users were acquired from each marketing campaign?” – testing understanding of JOINs between, say, a Users table and a Campaigns table (or simply grouping if campaign info is in the Users table).
• “What is the distribution of orders per user?” – expecting recognition of needing aggregation (perhaps a subquery counting orders per user, then stats on that).
• “How would you identify power users versus new users in the data?” – not a specific query, but describing what criteria to query (e.g., number of sessions or actions).

In essence, PM-oriented questions often describe analytics scenarios: you might be given a product usage scenario and asked which metrics or SQL queries you’d use to get insights. There’s often an implied narrative: “We launched Feature X – how would you use SQL to determine if Feature X increased engagement?”

A PM should know basic SQL conceptually. For example, understanding the idea of a JOIN (even if they might not code it perfectly) is useful to combine data from different tables. They should also know how to use GROUP BY for metrics. If an interviewer asks something like “how do you get the most active day of week from the user logs?”, a PM could answer: “I’d group user logins by day of week and count them​hellopm.co, then see which day has the highest count.” That demonstrates understanding of SQL’s capability without necessarily writing the exact syntax on the spot.

In summary, Product Managers should be ready for questions that test their ability to interpret and request the right data rather than write complex code. Showing that you can frame a question in SQL terms (e.g., “I’d filter for last month’s data and then group by feature usage”) and being comfortable with terms like join, filter, group, sum, average will typically suffice​hellopm.co. Some companies might not ask PMs to write SQL at all, but it’s good to be prepared to talk about how you’d get data to support product decisions.

For Data Analysts

Data Analysts live and breathe SQL, so interview questions for analyst roles can be more technical and detailed. Expect a mix of conceptual questions, query-writing tasks, and possibly questions about interpreting query results. Key areas of focus include:

• Joins and Data Transformations: Analysts are often asked to combine data from multiple tables. For example, “Given a sales table and a customers table, write a query to get total sales by customer region.” This involves a JOIN and a GROUP BY. The interviewer will be looking for correctness and maybe efficiency.
• Aggregations and HAVING: Questions like “Find departments with average salary above X” or “Which products have more than 100 orders?” require GROUP BY and HAVING clauses, which analysts should be fluent in​forums.sqlteam.com.
• Window Functions: Many analyst interviews include at least one question on window functions (analytic functions) since they are extremely useful for ranking, running totals, percentiles, etc. For example, “How do we get a running total of sales by day?” or “Identify the top 3 products in each category by revenue.” An analyst should be able to outline using ROW_NUMBER() or RANK() with PARTITION BY for the latter​codesignal.com​codesignal.com. They might even ask specifically, “What’s the difference between RANK() and DENSE_RANK()?” (an often-asked question for analysts, since these come up in reporting) – as an analyst, you should be ready to explain and give a quick example.
• Subqueries: Data analysts may get scenarios for using subqueries, like “Find employees who earn more than the average salary of their department” (as we solved earlier) or “Select customers who bought all products in category X” (which could use a subquery with a NOT EXISTS logic). Demonstrating clear use of subqueries or CTEs is important.
• Data Cleaning/Extraction: Analysts might be asked about string functions or date functions because a lot of real work involves cleaning up messy data. For instance, “Extract the domain from an email address” (using string functions) or “Convert a timestamp to just the date”. These are more straightforward but gauge your familiarity with SQL functions.

Example Analyst Question: “How would you find the median of a numeric column using SQL?” – This is interesting because SQL doesn’t have a built-in median in many databases. A strong answer: use window functions or percentile functions if available, or a subquery approach. An analyst might say, “I could use PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY column) in databases that support it, or use a CTE to rank values and pick the middle one.” It’s this kind of thinking that shows you know how to leverage SQL for statistical analysis.

Additionally, analysts should be comfortable explaining query results. An interviewer might show you a piece of SQL and ask “what does this result table represent?” They may also ask behavioral questions like how you’d approach a vague problem with data, where you’d likely outline an analysis plan that involves writing SQL at various steps.

To prepare: Focus on writing and understanding complex queries that involve multiple steps. Practice some window function queries (like moving averages, rankings)​codesignal.com​codesignal.com, as well as typical reporting queries (grouping, joining). Know your SQL functions (string, date, numeric) as analysts often have to use them. And be ready to optimize or discuss performance (like why an index on a certain column would help a query – this can sometimes come up if the role is more technical).

For Engineers (Developers and Data Engineers)

For engineering roles, SQL questions can be a mix of the above, but often with a twist toward database design, performance, or more complex problem-solving using SQL. Let’s differentiate a bit:

• Software Engineers/Backend Developers: They might get SQL questions to ensure they can interact with a database efficiently. Common questions include explaining normalization (to see if they understand how to design schemas), writing joins, or perhaps writing a moderately complex query involving a join and a subquery. They may also be asked about transactions and isolation levels if the role involves working with databases heavily (e.g., “What is a transaction? When would you use COMMIT/ROLLBACK?” or “Explain the difference between InnoDB and MyISAM” if MySQL, etc.). A backend engineer might also get a question on indexing for query performance: “We have a large users table and we run SELECT * FROM users WHERE email = ? often – how can we speed that up?” (Expected: “Add an index on the email column” and discussion of how indexes work). In coding interviews, backend engineers might be given a scenario to demonstrate SQL use within an application context, or even a simple database design question: “Design a schema for X”. They may also be asked to write a query joining 2–3 tables – similar to analyst questions, but possibly less focus on tricky window functions unless the job listing specifically mentions heavy data work.
• Data Engineers: They often face more SQL ETL scenarios and questions about handling big data. A data engineer interview might ask: “How would you transfer data from a staging table to a fact table, transforming it in SQL?” So, they might expect knowledge of INSERT...SELECT or MERGE statements, creating new tables, or using SQL for data cleaning. They could also be asked about window functions, since those are useful in data pipelines (e.g., deduplicating rows using ROW_NUMBER). Data engineers also might get questions about performance and indexing, or how to partition data in a database for faster access. Another area is SQL on big data frameworks (like Hive or SparkSQL) if relevant – but that’s usually beyond standard SQL interviews, unless specified.

In engineering interviews, you might also get more theoretical questions, such as:

• “What are normalization forms and when might you denormalize?” – As an engineer, you should know at least up to 3NF and why sometimes denormalization is used for performance.
• “Explain the difference between a clustered index and a non-clustered index.” – This is a classic when interviewing for roles involving SQL Server or similar (we covered this in the Q&A section)​simplilearn.com.
• “What’s an execution plan and have you ever used it to optimize a query?” – Engineers are sometimes expected to debug slow queries; knowing how to read an explain plan is a bonus.
• “How do transactions work and what are isolation levels?” – For roles dealing with concurrent data access, this could be asked. For example, describing READ COMMITTED vs REPEATABLE READ in terms of preventing dirty reads, etc., and possibly an example of a race condition that transactions prevent.

Example Engineer (Dev) Question: “Write a SQL script to add a new column to a Users table and backfill it based on data from another table.” – This tests both DDL (ALTER TABLE) and an UPDATE with a JOIN or subquery. A good answer: show the ALTER TABLE ... ADD COLUMN statement, then an UPDATE users SET new_col = (SELECT ... FROM other_table WHERE ...)​codesignal.com​codesignal.com. It shows you know how to modify schema and manipulate data.

Example Engineer (Data Engineer) Question: “You have a raw transactions table with possible duplicates. How would you write a SQL query to remove duplicates?” – One answer: use a window function like ROW_NUMBER() to identify dupes (partition by some natural key, order by maybe timestamp, then pick row_number = 1) and either select those or delete the rest. Or using DISTINCT if appropriate. Data engineers are expected to be savvy with such window function usage for data cleanup.

Engineers should also expect some questions about schema design or understanding relationships, because part of their job is often collaborating with database design. For instance, “Explain how you would design a database for a simple blog with users, posts, and comments.” They will look for proper tables (Users, Posts, Comments) with foreign keys (comments linked to posts, posts linked to users, etc.). While this strays into database design more than pure SQL querying, it’s fair game for many software engineering interviews.

In summary, Engineers should be prepared for a blend of: writing medium-complex queries, understanding deeper RDBMS concepts (indexes, transactions, normalization), and perhaps demonstrating knowledge of SQL in the context of application development or data pipelines (like writing a stored procedure, or handling an ETL in SQL).

As you can see, each role emphasizes different aspects of SQL:

• A Product Manager needs to comfortably talk about data and basic queries to get product insights​hellopm.co. Focus on clarity and knowing what to query for.
• A Data Analyst needs to be fluent in writing and explaining complex SQL for analysis – practice aggregation, joins, subqueries, and especially window functions which are a favorite in analyst interviews​codesignal.com​codesignal.com.
• An Engineer needs a solid grasp of writing correct SQL and understanding how databases work under the hood – be ready for schema design discussions, index and performance questions, and transaction handling​codesignal.com​codesignal.com.

Internal Tip: No matter the role, if you mention a term like “index” or “normalization” or “window function”, be prepared for a follow-up question on it. Tailor your study to the role: for example, a PM might spend more time on high-level SQL use cases, while an analyst drills down on practicing actual queries on sample databases, and an engineer reviews both query writing and database theory.

By understanding the focus areas for your target role, you can prepare more effectively and speak the interviewer’s language when those SQL questions come up. Good luck!