SQL Interview Prep Guide for Data Analysts & Data Engineers

Preparing for a SQL interview doesn’t have to be stressful. Early-career data analysts and engineers often face a SQL or data engineering screen as the first technical hurdle, and it can feel overwhelming. The good news is that with the right prep strategy, you can absolutely nail it (SQL Interview Prep: 24 Essential Questions, Answers + Code Examples | Zero To Mastery). This guide will walk you through what to expect, how to master key SQL concepts, and tips to ace the SQL coding interview. We’ll also highlight specific considerations for data engineering roles and point you to some great resources (like Galaxy’s SQL Interview Hub and Top Data Jobs board) to further boost your prep.

What to Expect in a SQL Coding Interview

SQL interviews often involve solving query problems under observation. As HubSpot’s analytics team notes, the SQL interview is one of the most common technical interviews for early-career analysts (Six Tips to Ace an Analyst SQL Interview). It usually works like this in a live interview setting:

• You’ll be given one or more tables (often a simplified schema relevant to the business) and a question to answer using those tables.
• You’re asked to write SQL logic – often on a whiteboard or in a simple editor – that may not actually execute the query. (Some companies provide a laptop or online platform, but many just want to see your thought process on paper.)
• The interviewer will encourage you to “think out loud” as you formulate the query, explaining your approach and assumptions.
• Initial questions start easy and then ramp up in difficulty, sometimes building on the earlier results.

Importantly, you might not get to run the query for correctness during the interview. Some companies have you write the query in a shared document or whiteboard and talk through it. In these cases, explaining what you are doing and why often matters more than getting the perfect answer immediately. Interviewers want to see how you approach problem-solving in SQL, not just the final query.

Take-home SQL challenges or online SQL assessments are another format. These allow you to run queries on a dataset (often on platforms like HackerRank or an in-house tool). If you have a take-home assignment, you’ll be expected to write working queries and possibly optimize them for efficiency. But in any format, the core skills tested are the same: can you independently write correct, efficient SQL queries and interpret the results? This is what the SQL interview aims to answer.

Pro Tip: Treat the interview like a collaboration. Don’t hesitate to ask clarifying questions about the data (e.g. “Is this table at the user level or account level?”). In fact, taking notes about the table schemas and asking about anything unclear is encouraged. Also, narrate your thought process as you go. Even if you feel awkward speaking while coding, remember that interviewers give partial credit for logical reasoning – they can’t do that if you stay silent. It’s perfectly fine to pause and collect your thoughts (just say “Give me a moment to think this through”), then explain the steps you’re considering. SQL interviews can feel like an exam with someone watching your every move, but that’s normal. Embrace a bit of awkwardness and focus on the problem.

Essential SQL Topics to Master

No matter how the interview is conducted, you’ll need a solid grasp of SQL fundamentals. In fact, most SQL interview questions focus on core querying skills rather than obscure syntax. Here are the must-know topics you should review:

• SELECT Queries and Filtering: Make sure you know how to retrieve data with SELECT and filter results with WHERE clauses. Understand logical conditions (AND, OR, NOT) and how to handle NULLs in comparisons. These basics form the backbone of any SQL question.
• JOINs (and Types of Joins): Joins are extremely important. Practice how to combine tables with different join types – INNER JOIN, LEFT (OUTER) JOIN, RIGHT JOIN, and FULL OUTER JOIN. Know what each join returns (e.g. inner joins only matching rows, left joins including all rows from the left table, etc.). Many interview questions revolve around correctly joining multiple tables. It’s common for a slightly tricky join condition to be the part that “ruins absolutely everything” if done wrong! Also be aware of self-joins (joining a table to itself) and the concept of anti-joins (finding records in one table not matching another). You should be able to explain when to use each type of join.
• Aggregation and GROUP BY: Any role that uses SQL will expect you to aggregate data. You should confidently use aggregate functions like COUNT, SUM, AVG, MIN, MAX along with GROUP BY to summarize data. Remember that when you use aggregates, you must include a GROUP BY for non-aggregated columns. A classic interview task, for example, is “find the count of records per category” or “sum sales by month”. Also know the difference between filtering with WHERE (filters rows before aggregation) vs. HAVING (filters groups after aggregation).
• Aliases and Query Structure: Use column aliases and table aliases to make your SQL more readable – and know where you can and cannot use them. (For instance, you can’t refer to a SELECT alias in the WHERE clause in most SQL dialects.) Clear aliases will help you and the interviewer follow your query logic. Structure your query in the typical SQL order: SELECT -> FROM -> JOIN -> WHERE -> GROUP BY -> HAVING -> ORDER BY. It sounds basic, but interview stress can cause confusion – writing a quick outline of the query structure can keep you on track.
• ORDER BY and LIMIT: Be comfortable sorting results and picking top-N results. A common challenge is “find the top 3 records in each group” which combines ranking functions or creative use of subqueries with ORDER BY. At minimum, know how to sort and use LIMIT (or TOP in T-SQL) to get a subset of results.
• Subqueries and CTEs: Many interviews include questions about subqueries, or even require them in a solution. Practice both nested subqueries (a subquery inside a WHERE or FROM clause) and correlated subqueries (subqueries that reference the outer query’s data). Know how to use a Common Table Expression (CTE) (WITH clause) to break a complex query into parts. In fact, using CTEs can greatly improve the clarity of your SQL – interviewers appreciate readable queries. One Reddit commenter specifically noted that CTEs are good to brush up on, including when to use them (e.g. to replace subqueries in some cases).
• Window Functions: For many analyst and engineering roles, window functions are the next level of SQL skill that interviews probe. Window functions (also known as analytic functions) like ROW_NUMBER(), RANK(), DENSE_RANK(), LAG()/LEAD() allow you to perform calculations across sets of rows related to the current row. Interviewers love asking about ranking and running totals. It’s almost certain you’ll encounter a window function question in intermediate-level SQL interviews. For example, you might be asked to “find the second highest value in each group” or use ROW_NUMBER() to remove duplicates. Make sure you understand the syntax (OVER (PARTITION BY ... ORDER BY ...)) and can explain the difference between RANK() and DENSE_RANK(). Even if you have to look up exact syntax on the job, in an interview you should demonstrate familiarity with these powerful functions.
• SQL Functions and Date Manipulation: Be aware of common built-in functions for strings (like LOWER(), LEN()/LENGTH()) and dates (DATEADD, DATEDIFF, etc.), especially if the role involves time-series data. You don’t need to memorize every date function across SQL dialects – interviewers usually won’t fault you for minor syntax slips, given date functions vary by database. However, know the concepts: how to extract parts of a date (YEAR(date) or EXTRACT()), how to do date arithmetic (adding or subtracting intervals), and how to format dates. Often, a question might ask “how would you get all records from the last 7 days?” which can be solved with a date function or a WHERE clause using date arithmetic.
• Primary Keys, Foreign Keys, and Joins Relationships: On the conceptual side, be clear on what a primary key and foreign key are, and how they relate tables. While this might not be asked directly, it underpins your understanding of joins. You should also know terms like referential integrity (at least at a high level) and understand why duplicates might appear when joining (e.g. one-to-many relationships).
• Indexes and Performance Basics: For more engineering-focused roles, you might get a question like “How would you speed up a slow query?” or “What is an index and how does it help?” Be ready to discuss the purpose of indexing and the trade-offs (faster reads, slower writes, and additional storage). Also, know the difference between a clustered index vs. non-clustered index if you’re aiming for a data engineering position. You generally won’t have to design an index in a live coding interview, but showing that you understand how data is stored and optimized will set you apart.
• Normalization and Database Design: You might be asked conceptual questions about database design – especially for data engineering roles or if the interview is more theoretical. Be ready to define normalization (and why it’s used to reduce data redundancy) and perhaps discuss normal forms. For instance, an interviewer could ask, “What are the pros and cons of normalizing your database schema?” or give a scenario to identify if a design is normalized. Understanding normalization vs denormalization and when each is appropriate is valuable (denormalization often comes up in data warehousing discussions). If you’re interviewing for a data engineering role, topics like normalization and data modeling are considered must-know.
• SQL Command Types (DDL, DML, DCL, TCL): It’s useful to know the categories of SQL commands. This might come up in a question like “What are the different types of SQL commands?” – where you’d answer: DDL (Data Definition Language, e.g. CREATE/ALTER tables), DML (Data Manipulation Language like INSERT, UPDATE, DELETE), DCL (Data Control Language like GRANT/REVOKE permissions), TCL (Transaction Control Language like COMMIT/ROLLBACK), and of course DQL (Data Query Language – basically the SELECT and query part). A data engineer is expected to know these and be able to discuss creating and altering tables, not just querying. Review how transactions work and what happens when you COMMIT or ROLLBACK, just in case.

As you can see, the range of topics spans from basic select/join/aggregate logic to more advanced optimization and design considerations. If that feels like a lot, remember that most interviews prioritize fundamental query logic and problem-solving. SQL exercises are focused on fundamental logic, since more complicated statements can be learned fairly quickly (or sometimes accomplished through simpler statements). In other words, if you can demonstrate solid SQL reasoning on the core topics above, you’ll be in great shape. Make a checklist of these topics and ensure you can answer questions or solve problems in each area. If any of them sound unfamiliar, that’s your cue to do a bit of refresher study before the interview.

Practical Preparation Strategies for SQL Interviews

Knowing what to study is one thing – but how do you prepare effectively? Here are some proven strategies to level up your SQL skills and confidence before the interview:

• Review and Solidify SQL Basics: Start by reviewing basic SQL syntax and definitions, especially if it’s been a while since you learned them. Ensure you can answer “What is SQL?” and explain key concepts in simple terms. It may help to read through a list of common SQL interview questions and answers. DataCamp’s Top 85 SQL Interview Questions and Answers is a great comprehensive resource covering everything from basic definitions to advanced queries. Make sure you understand the answers, rather than memorizing them, so you can adapt that knowledge to any question phrased differently.
• Practice Writing Queries Regularly: There is no substitute for hands-on practice. Set aside time each day leading up to the interview to write SQL queries. Use online platforms with interactive SQL practice problems to simulate the interview experience. For example, LeetCode, HackerRank, StrataScratch, and DataLemur all offer a collection of SQL challenges of varying difficulty. In fact, many candidates and interviewers recommend these platforms – StrataScratch and LeetCode have a good collection of SQL problems with varying difficulty levels and can help you ace your interview (Need Advice for My First Coding Interview on SQL - Reddit). On these sites, you can practice the exact kind of questions asked in interviews (some even tagged by company). A smart approach is to search for the company name on StrataScratch or DataLemur – often you’ll find actual past interview questions from Company X, which gives you insight into what they might ask.
• Simulate the Interview Environment: When practicing, sometimes turn off the execution engine – try writing queries on paper or a whiteboard to mimic the pressure of not being able to run the query. This will train you to think through the logic carefully. Also practice explaining your solution as if an interviewer were listening. You can even record yourself or talk to an empty room (it might feel silly, but it helps!). Alternatively, pair up with a friend or colleague for a mock interview: have them pose a SQL question, share a blank screen or whiteboard, then talk through solving it in real-time. This kind of mock interview practice is invaluable for getting comfortable with articulating your thought process and receiving feedback.
• Engage with Real-World Scenarios: Beyond textbook problems, challenge yourself with real data questions. Kaggle datasets or public data can be great for coming up with your own questions to answer with SQL. For example, take a dataset and try to come up with queries an interviewer might ask (e.g. “Find the top 5 most active users each month” on a user activity dataset). This will help you think critically about problem-solving in a practical context. Being comfortable with case studies can help you on questions where you need to design or optimize queries for a scenario.
• Brush Up on Database Concepts and Optimization: As part of your prep, revisit how indexes work, how transactions are managed, and other database fundamentals (especially for data engineering interviews). You don’t need super in-depth DBA knowledge, but you should be able to have a conversation about why an index might improve a query, or what the difference is between deleting rows and truncating a table. These are common conceptual questions for intermediate candidates. Similarly, understand basic optimization techniques (e.g., avoiding SELECT * in production queries, using appropriate WHERE filters to limit data early, etc.). Some interviews might ask “How would you approach optimizing this slow query?” – be ready with a few suggestions (add an index, rewrite using a different approach, etc.).
• Use Cheat Sheets for Last-Minute Review: In the days before your interview, it can help to condense the info into a cheat sheet. Galaxy’s SQL Interview Hub provides a handy Ultimate SQL Cheat Sheet Collection for modern SQL, which is great for quick refreshers on syntax. DataLemur also offers an SQL interview cheat sheet. Skimming a cheat sheet can quickly remind you of, say, the syntax for a window function or the order of JOIN vs WHERE vs HAVING if you mix those up. Just don’t rely on it during the interview, of course – it’s only for your prep. (One neat trick: if you often forget a particular detail, write it down by hand. The act of writing can help cement it in memory.)
• Stay Updated on SQL Dialects (if relevant): If you know what SQL flavor the company uses (MySQL, PostgreSQL, Oracle, etc.), it’s worth checking if they have any unique functions or quirks. For example, BigQuery has some differences from standard SQL, Oracle has the ROWNUM pseudocolumn instead of LIMIT, etc. However, do not stress too much on dialect differences – as noted earlier, interviewers usually don’t mind if you use slightly incorrect syntax for a specific flavor, as long as your intent is clear. If you’re unsure, you can mention which dialect you’re most familiar with. (E.g. “In MySQL I’d use LIMIT 10 here – I believe in T-SQL the equivalent would be SELECT TOP 10. Just calling that out.”) This shows awareness and honesty about your experience.

Finally, practice, practice, practice – especially with JOINs! As one seasoned analyst put it, being really good at writing SQL queries comes down to lots of practice, and joins are often the trickiest part that trip people up. Make sure you’ve written plenty of join queries (including multi-join queries) before you interview. Also practice a few “thinking on your feet” problems – e.g., write a query that finds the second highest salary, or a query that transposes rows to columns – so you get used to solving novel problems. The more problems you solve in practice, the more confident you’ll feel when a new question comes your way in the interview.

Tips to Ace the SQL Interview (Beyond the SQL itself)

Technical skills aside, there are some general interview best practices that can significantly boost your performance in a SQL interview:

• Clarify the Requirements: When the question is presented, repeat it back in your own words to ensure you understand it correctly. For example, “So, I need to find the total sales per region for the last quarter, and then identify which region had the highest sales, is that right?” This gives the interviewer a chance to correct any misinterpretation before you start. It also buys you a moment to think about the approach.
• Plan Your Approach Out Loud: Before diving into writing the full query, outline how you intend to solve the problem. You might say, “First, I’ll aggregate the sales by region and quarter, then I’ll filter to last quarter’s results, and finally sort to get the top region.” This shows the interviewer your logical thought process. Speaking your thoughts has another benefit: if you go down the wrong path, the interviewer can gently nudge you back on track or clarify something, since they see where your thinking is headed. Remember, they’re evaluating your problem-solving method as much as the final answer.
• Work Incrementally if Possible: If it’s a live coding scenario and the environment allows, build the query step by step. For instance, you might start by selecting from one table to ensure you recall the columns, then add a join, then add the aggregation, and so on. Explain each step: “I’ll start by joining the tables to make sure I get the dataset I need, then I’ll add the grouping.” This way, if a mistake creeps in, you can catch it earlier. On a whiteboard you can’t run the query, but you can still write it in stages and double-check each part as you add it.
• Pay Attention to Detail – But Don’t Obsess: SQL syntax and formatting can be finicky, but interviewers usually aren’t grading you on semicolons or perfect capitalization. In fact, “some things don’t matter” – they’re not testing your ability to memorize exact syntax or write beautifully formatted code under pressure. If you blank on a specific function name, it’s okay to say, “I’d use the date function here to get the year, forget the exact name in Oracle, but let’s call it YEAR() for now.” That said, do try to avoid actual syntax errors that reflect misunderstanding (mixing up WHERE and HAVING, for example, would signal a gap in knowledge). Write clearly and organize your query for readability, but don’t panic if you momentarily forget whether it’s SUBSTRING or SUBSTR – focus on the logic, and the interviewer will understand your intent.
• Use Meaningful Naming and Structure: If writing a complex query, use indentation and line breaks to organize it (especially for joins and subqueries/CTEs). Label parts of the query with aliases that make sense (alias subqueries as customer_totals instead of t1, for example). Interviewers appreciate clean, readable queries. Not only does this reduce chances of mistakes, it also showcases a skill you’d use on the job – writing maintainable SQL. If you make an assumption (like “assuming no duplicate entries for a user in this table”), you can even jot a short note in the query or verbally note it. It demonstrates you’re considering edge cases.
• Keep an Eye on Time and Hints: SQL interviews are often timed. If you find yourself stuck, it’s better to ask for a hint or think of a simpler approach than to stay silent or spin in circles. For instance, if you can’t remember how to do a certain join trick, you might say, “I’m a bit stuck on getting this partition logic right – I might try another approach to solve this,” or ask, “Is there a particular function you’d like to see here? I’m considering using a window function.” Interviewers will often give a nudge if you’ve shown good effort. They’d rather see you succeed with a hint than fail in silence. Just make sure you’ve made a genuine attempt first.
• Validate Your Output Mentally: After writing the query, do a mental walkthrough with a small data example if possible. Explain: “Let’s imagine Table A has 2 rows and Table B has 3 rows…” and step through the query logic to see if it produces the expected result. This can help you catch any logic errors. It also shows thoroughness. If the interview format allows it, you might get to actually run the query on sample data – in that case, definitely check your output and be ready to explain if it doesn’t look right.
• Demonstrate SQL Best Practices: Little things can impress. For example, explicitly specify columns in your SELECT (avoid SELECT *) if appropriate, to show you’re mindful of not pulling unnecessary data. If you know a join could multiply rows, mention that you’d consider if a DISTINCT or additional condition is needed. These are the kind of thoughtful touches that interviewers remember. Just don’t go overboard – do what’s relevant for the question at hand.
• Stay Calm and Positive: Finally, keep your cool and be confident in your preparation. If you prepared with a variety of practice problems, you’ve likely seen harder questions than what you’ll get in the interview. In the moment, if you feel stuck or make a mistake, don’t let it frazzle you. Take a breath, acknowledge it (“Oops, you’re right, that join would duplicate data – let me correct that”), and carry on. A calm demeanor under pressure is a plus. By practicing out loud and simulating the interview ahead of time, you’ll be much more comfortable when it’s the real deal.

Remember, interviewers aren’t trying to trick you. They want you to succeed and show your best skills. Even if you don’t solve 100% of the question, a methodical approach and clear explanation can still leave a great impression. And if you do blank on something trivial, don’t sweat it – it happens. Focus on demonstrating how you break down the problem and handle data, because that’s what ultimately matters in day-to-day work.

SQL in Data Engineering Interviews – What’s Different?

If you’re preparing for a data engineering interview, all the SQL tips above apply, plus a bit more. Data engineers are expected to be even more fluent in SQL because they work closely with large datasets and set up the infrastructure that analysts and others rely on. In fact, to be a good data engineer, you really need to be an SQL master.

Here are some additional things to keep in mind for data engineering roles:

• Expect Advanced SQL Questions: Data engineering interviews will often include the same kind of SQL questions given to analysts (joins, aggregates, etc.), but might push further into advanced SQL territory. You might see more complex scenarios involving window functions, multiple subqueries/CTEs, or questions that blend SQL with understanding of data workflows. For example, an interviewer could ask you to write a query that performs an ETL-like transformation, or to solve a problem that involves a lot of data wrangling using SQL. Be prepared for a “twist” in SQL challenges, like handling semi-structured data (JSON in SQL) or writing a recursive CTE (common in interviews to traverse hierarchical data).
• Database Modeling Knowledge: Unlike an analyst, a data engineer is usually asked about data modeling and schema design. You should be ready to discuss how you’d design tables for a new application, how you would use normalization in OLTP databases versus denormalization in OLAP/analytics databases, etc. Know your normal forms and be able to give an example of a normalized design. They may ask conceptual questions like “What’s the difference between a star schema and a snowflake schema?” or “How would you design a database for a library system?” Showing that you understand relational design principles is key.
• DDL and DML Mastery: Data engineers often write the DDL (Data Definition Language) statements to create or alter database structures. So, an interview could include writing a CREATE TABLE statement or an ALTER TABLE to add a constraint. Make sure you remember how to define data types, primary/foreign keys, and indexes in SQL DDL. You might also be asked how you’d manage schema changes or handle migrations of data. Understanding transactions and the importance of things like foreign key constraints could come up here.
• SQL at Scale and Optimization: Be prepared to talk about querying large datasets efficiently. Even if the interview problem itself isn’t huge, the interviewer might ask, “How would this query behave with 100 million records? How would you optimize it?” Have answers ready such as adding proper indexes, partitioning data, avoiding unnecessary computations, etc. Also, if you have experience with a particular SQL engine (like Hive, Spark SQL, Redshift, BigQuery), think about optimizations in those environments (like using partition keys in Hive/Redshift or clustering in BigQuery). Data engineering interviews might also touch on query execution concepts – not in a super theoretical way, but maybe “What does the query planner do?” or “Why might a WHERE clause on a non-indexed column be slow?”. Demonstrating an understanding of the why behind SQL performance will set you apart.
• Data Integration and ETL using SQL: Many data engineers use SQL for data transformation in ETL pipelines. You might get a question that is essentially a mini-case: “We have raw clickstream data in one table and user info in another; how would you transform and join them to create a daily activity summary table?” This is basically a SQL problem, but framed as an engineering task. Be ready to outline how you’d use SQL to accomplish such tasks (maybe using multiple steps or temp tables/CTEs). They might also ask about tools, but if you answer in terms of SQL logic, that’s fine.
• Security and Access Control: In some cases, data engineering interviews include questions on data governance. Know the basics of SQL security controls – what are roles and permissions, what does GRANT do, etc. This is related to DCL (Data Control Language). You might not be asked to write a GRANT statement, but understanding how you’d allow one team access to a view but restrict raw table access, for example, could come up in conversation.
• Discuss Your Experience with SQL in Engineering Projects: Be prepared to talk about how you’ve used SQL in your past projects. Data engineering interviews often have a portion where they ask about your experience building data pipelines or databases. Highlight any significant SQL work you did – maybe you wrote complex queries for data quality checks, or you optimized a slow query that was delaying a pipeline, or you designed a schema for a new data warehouse table. Concrete examples will back up your skill. If you’re transitioning from an analyst role, emphasize the times you dealt with performance or modeling, since those resonate with engineering concerns.

In short, a data engineering interview guide would tell you that SQL is foundational but not the whole story – you also need to show you can apply engineering rigor around it. As one guide puts it, many SQL questions for data engineers are the same as those for analysts/scientists, but data engineers are expected to know them at an advanced level and also handle database design and manipulation beyond just SELECT queries. So ensure you review both your querying skills and the bigger picture of working with databases.

Resources and Next Steps

With solid preparation, you’ll be ready to tackle SQL interviews with confidence. As a recap, focus on mastering SQL fundamentals, practice extensively (particularly on realistic interview questions), and communicate clearly during the interview. Each interview you go through will also make you better for the next one – it’s a bit of a game of chance and practice, and the more you interview, the better you get.

To further boost your prep, take advantage of the wealth of resources out there. Galaxy’s SQL Interview Hub is an excellent one-stop shop: it offers a curated collection of 100+ real SQL interview questions (from sources like DataCamp, Reddit, FAANG interviews), complete with answers and cheat sheets for quick review. These resources cover everyone from beginners to advanced users, and even break down SQL topics by role. It’s a great way to verify you’ve covered all your bases, and you might encounter some of the exact questions you practice when you go in for the real interview!

Finally, once you’ve aced that SQL interview, you’ll want to put those skills to use. If you’re on the job hunt, check out Galaxy’s Top Data Jobs board for the latest openings in data engineering, analytics, and data science at top companies. You can find remote and entry-level roles, and see what real job descriptions are asking for (hint: SQL is almost always on the list!). It’s a smart way to tailor your preparation to the roles you’re aiming for – and who knows, you might find your dream job there.

Good luck with your SQL interview prep! With a balanced study plan focusing on both theory and practice, and by following these tips, you’ll be well on your way to writing query answers that impress your interviewers. Remember, mastering SQL is a journey – each problem you solve is a step toward becoming that go-to data professional who can wrangle data from any database. You’ve got this! 🚀