The Microsoft Data Engineer Interview Guide (Updated for 2024)

The Microsoft Data Engineer Interview Guide (Updated for 2024)The Microsoft Data Engineer Interview Guide (Updated for 2024)


Microsoft has been pushing boundaries in tech for a while now. Apart from their recent bold foray into AI, they are expected to continue to make strides in their businesses ranging from gaming to cloud computing. All this innovation means that they need to recruit top talent, and that’s why they need more data engineers in 2024.

With attractive pay, good work-life balance, and great health benefits, Microsoft is a generous and flexible employer.

In this detailed guide, we’ll demystify the Microsoft Data Engineer interview process for you. Most importantly, we’ll cover a wide range of questions that are popularly asked in Microsoft interviews and give you tips on tackling them like a pro.

What is the Interview Process Like for a Data Engineer Role at Microsoft?

This role will test your expertise in data modeling, coding, and, most importantly, problem-solving. Further, they want engineers who can communicate well and demonstrate passion and curiosity. Cultural fit is also important, so make sure to prepare responses for common behavioral questions.

Please note that the questions and structure of the interview process will differ based on the team and function advertised in the job description. Always go through the job role carefully while preparing your interview strategy.

Microsoft’s interview process can take anywhere between 4 weeks to 3 months.

Step 1: Preliminary Screening

A recruiter would call you to get a sense of your work experience and your cultural fit. They may ask you why you want to join Microsoft and a couple of questions related to past projects, so prepare some canned responses based on your research about the company and past projects.

Step 2: Technical Assessment

Successful candidates then undergo one or two technical interviews, usually via video chat. This is often a live coding round on a shared whiteboard. You may be asked to demonstrate your engineering knowledge through scenario-based case studies as well.

Step 3: Onsite Interviews

If it’s a good fit, you will be invited onsite to meet your team and have a few rounds of interviews. These typically involve a mix of technical, behavioral, and case study questions. You can expect an entire round devoted to architecture and design questions.

Step 4: Final Interview

The final stage usually involves meeting with senior-level executives or team leaders. This last round will assess your cultural fit and your motivation to join the firm.

What Questions Are Asked in a Microsoft Data Engineer Interview?

Microsoft’s data engineering interview questions primarily focus on practical skills in data manipulation, query optimization, and algorithm design, along with problem-solving in real-world data engineering scenarios. The questions are designed to test technical expertise, analytical thinking, and the ability to apply knowledge in practical situations relevant to Microsoft’s data engineering challenges.

For a more in-depth look at these questions, let’s go through the list we have below:

1. Given a list of integers, write a function to find the greatest common denominator between them.

This question assesses your understanding of basic algorithms and number theory, both fundamental for Microsoft data engineers who need to manipulate and analyze large datasets.

How to Answer 

Explain the concept of GCD (Greatest Common Denominator) as the largest number that divides all integers in the list evenly. Choose an efficient algorithm, like the Euclidean algorithm, and outline its steps. Briefly mention how you would handle edge cases like empty lists or negative numbers.


“The greatest common denominator (GCD) of a list of integers is the largest number that all the elements are divisible by. An effective approach would be the Euclidean algorithm, which repeatedly divides the larger number by the smaller until the remainder is 0. The final divisor is the GCD.

It’s important to consider edge cases like empty lists, where the GCD wouldn’t be defined. We can handle this by setting the GCD to 0 for an empty list. Additionally, we need to ensure the algorithm works for negative numbers: simply converting all negatives to positives before applying the Euclidean algorithm can address this.”

2. Let’s say we have a table with ‘ID’ and ‘name’ fields. The table holds over 100 million rows, and we want to sample a random row in the table without throttling the database. Write a query to randomly sample a row from this table.

At Microsoft, engineers need to be able to efficiently query and sample from large datasets. This question assesses your ability to optimize queries considering Microsoft’s platform functionalities and performance priorities.

How to Answer 

Briefly mention how full table scans can be detrimental to database performance, especially when dealing with millions of rows. Highlight one or two approaches like OFFSET with random numbers and reservoir sampling (Knuth’s algorithm). Briefly explain their core concepts and suitability for the given scenario, and finally, choose the method you think is most optimal for Microsoft’s context.


“Given its alignment with efficient database querying and its utilization of standard SQL functions, I’d prioritize the OFFSET method for Microsoft’s context. However, if memory constraints are tighter, reservoir sampling could be a valuable alternative.”

3. We have a table representing a company payroll schema. Due to an ETL error, the employees table, instead of updating the salaries when doing compensation adjustments, did an insert instead. The head of HR still needs the salaries. Write a query to get the current salary for each employee.

Troubleshooting and fixing such data issues will be part of your day-to-day as a data engineer at Microsoft.

How to Answer

Mention the use of SQL constructs like subqueries, window functions, or GROUP BY clauses. Your explanation should demonstrate your ability to write efficient SQL queries.


“To get the current salary for each employee from the payroll table, I would use ROW_NUMBER() over a partition of the employee ID, ordered by the salary entry date in descending order. This ordering ensures that the most recent entry has a row number of 1. I would then wrap this query in a subquery or a Common Table Expression (CTE) and filter the results to include only rows where the row number is 1. This method ensures that only the latest salary entry for each employee is retrieved, correcting the ETL error that caused multiple inserts.”

4. Given n dice, each with m faces, write a function to make a list of all possible combinations of dice rolls. Can you also do it recursively?

Microsoft Data Engineers frequently handle tasks involving simulations or probabilistic calculations, for example, while creating scalable data processing solutions. This question is designed to see how you translate complex logical problems into implementable code.

How to Answer

Define the function and briefly describe your approach, for example, to utilize built-in functions to efficiently generate all individual face value combinations and yield each as a tuple. It’s also beneficial to mention the trade-offs between iterative and recursive solutions in terms of readability and performance.


“For massive datasets, efficiency should be prioritized with an iterative approach like the product function. It will generate all individual face value combinations and yields them as tuples, minimizing runtime and maximizing performance.”

5. Imagine you’re designing a product for Slack called “Slack for School.” What are the critical entities, and how would they interact? Imagine we want to provide insights to teachers about students’ class participation. How should we design an ETL process to extract data on student interaction with the app?

You need to be able to design data-driven solutions for such real-world scenarios. A data engineer at Microsoft will have to understand user requirements, conceptualize data structures, and create efficient extraction and transformation processes.

How to Answer

Your answer should clearly outline your understanding and scope of a “Slack for School” environment and the role of data in enhancing its functionality. Ask clarifying questions to identify critical entities, and make sure you state your assumptions clearly.

Example Answer:

“In “Slack for School,” the critical entities would include students, teachers, classes, messages, and participation metrics. Students and teachers interact through messages within classes. To provide insights into students’ participation, we would need an ETL process that extracts data on message frequency, response times, and interaction types (like questions, answers, or comments). This data would be extracted from Slack’s API, transformed to categorize and quantify participation levels, and loaded into a data warehouse where teachers can access summarized reports. This process ensures that teachers receive meaningful and actionable insights about student engagement in their classes.”

6. Write a function that takes a sentence or paragraph of strings and returns a list of all its bigrams in order.

Microsoft data engineers often deal with large volumes of textual data. This question tests your NLP (Natural Language Processing) skills, which are essential for text analysis.

How to Answer

Explain your method for generating bigrams, emphasizing efficiency and scalability, which are crucial in dealing with large datasets— common in Microsoft’s environment.


“I would write a function that splits the input text into individual words (tokens). This is typically done using the split() function in Python, which splits the text based on spaces. Once we have a list of words, the function iterates through this list to create bigrams.”

7. Let’s say you have analytics data stored in a data lake. An analyst tells you they need hourly, daily, and weekly active user data for a dashboard that refreshes every hour. How would you build this data pipeline?

This question is relevant in a Microsoft data engineer interview because it assesses your ability to design a data pipeline tailored to meet specific business requirements. It also tests your understanding of data processing and scheduling, which are critical skills in engineering teams.

How to Answer

Explain your approach to handling time-series data, ensuring data accuracy and timeliness, and selecting appropriate tools. Mention how you would schedule and automate the pipeline to refresh data.


“I would use Azure Data Factory to pull user data from the lake. The transformation stage could be efficiently handled using a distributed processing system like Azure Databricks. For the loading stage, I would use Azure Synapse Analytics to store the transformed data, as it allows for the quick retrieval of data, which is essential if we need to refresh it every hour. Additionally, I would implement monitoring and logging to track the pipeline’s performance and quickly address any issues.”

8. Write a SQL query to create a histogram of the number of comments per user in a particular month.

Microsoft’s ecosystem often involves analyzing user interactions on platforms like LinkedIn, Xbox, or Microsoft Teams. The question tests the ability to create actionable insights from data; a key responsibility in engineering roles.

How to Answer

Focus on the use of date functions and the aggregation method you would use. Relate your answer to a scenario relevant to Microsoft’s products or services where analyzing user engagement is important, such as in understanding platform usage patterns.


“In the query, I would filter the records based on the comment_date *to include only those from the relevant month. I would then group the data by user_id and count the number of comments for each user.”

9. Let’s say you have a table with a billion rows. How would you add a column inserting data from the source without affecting the user experience?

This question assesses your expertise in large-scale data operations in a live environment. Microsoft’s ecosystem often involves handling big datasets in products like Azure SQL Database or services that power platforms like LinkedIn.

How to Answer

Focus on methods like partitioning, batch processing, and leveraging features unique to Microsoft’s database systems. Discuss the importance of planning, testing in a non-production environment, and monitoring the impact on performance.


“I would first test the process in a controlled environment, like a replica of the production database in Azure SQL Database or SQL Server. I would utilize batch processing to add the column, dividing the operation into smaller, manageable parts. Conducting the update during off-peak hours is essential to minimize the impact on users, especially for services with global reach.”

10. How would you diagnose and optimize a slow-running SQL query in a Microsoft SQL Server environment?

This question is popular in Microsoft data engineer interviews because it assesses your SQL expertise and performance-tuning skills. Optimizing slow-running queries is essential to maintain database performance in large-scale environments typical at Microsoft.

How to Answer

Your answer should demonstrate a systematic approach to diagnosing SQL queries. Mention the use of techniques like query execution plans, indexing, and SQL Server performance counters.


“I would analyze the query execution plan to identify bottlenecks, such as full table scans or inefficient joins. Next, I’d add or optimize indexing to improve retrieval efficiency. Simplifying the query by reducing unnecessary joins and subqueries can also be effective. I would review SQL Server performance counters to ensure the issue isn’t related to broader server-level problems like CPU, memory, or disk I/O constraints.”

11. Imagine we’re migrating a legacy database to Azure SQL Database. What steps would you take to ensure a smooth transition, and how would you handle potential data inconsistencies?

This type of experience as a data engineer would be extremely valuable as Microsoft would have ongoing projects involving migration from legacy systems to cloud-based ones. It is imperative to ensure minimal disruption to enterprise-scale applications.

How to Answer

Include pre-migration assessment, migration planning, execution, and post-migration validation in your proposed plan. Mention how you’d deal with inconsistencies and discuss methods to minimize downtime during migration.


“I’d start with a thorough assessment to identify compatibility and data format issues. The planning phase would involve selecting appropriate migration tools like Azure Database Migration Service and strategizing for data consistency checks. During execution, I’d use parallel processing for minimal downtime and implement validation checks for data integrity. I’d focus on extensive testing after completing the migration to ensure full functionality and accuracy.”

12. If you’re working on integrating on-premises data storage with Azure cloud services, what factors would you consider, and what approach would you take for a seamless integration?

This question is pertinent in a Microsoft data engineer interview to assess your understanding of hybrid cloud solutions, a key area in Microsoft’s cloud strategy. It’s relevant for integrating legacy systems with Azure services for Microsoft’s diverse range of clients so that they can leverage cloud scalability while also retaining on-premise systems.

How to Answer

Your answer should cover the considerations for integration, such as data security, network connectivity, compliance, and synchronization. Also, discuss the use of specific Azure tools to facilitate this integration.


“Key considerations would include secure network connectivity, which can be achieved through Azure ExpressRoute. I would use Azure Security Center to align with security standards and regulations. For data synchronization, Azure Data Factory can create a seamless data movement pipeline. I’d also ensure the architecture supports elastic scaling to handle variable workloads.”

13. You have a database table Sales in SQL Server, containing columns ProductId, SaleDate, Region, and Amount. The table has millions of rows. You are asked to write an SQL query to find the total sales amount for each product by region for the last quarter, sorted in descending order. How would you write and optimize this query?

The ability to navigate big datasets and write efficient queries is crucial for supporting decision-making processes quickly, for instance, when another team is relying on Microsoft engineers to provide data promptly.

How to Answer

Mention using WHERE clauses for filtering data to the last quarter and GROUP BY for aggregation. It’s important to demonstrate your advanced understanding of query optimization, so briefly discuss indexing strategies to improve performance.

Example Answer:

“I would ensure the SaleDate, ProductId, and Region columns are indexed as indexing is key in speeding up query execution. The query would contain WHERE, GROUP BY, and ORDER BY clauses to meet the requirement of sorting by total sales amount.”

14. Let’s say that you need to analyze a large JSON file containing log data from a web application. Describe the steps and the Python libraries you would use to read, process, and aggregate the data. Also, explain how you would handle any data anomalies.

Microsoft, with its vast array of web-based services and applications, often requires engineers to work with complex data formats like JSON. The question tests skills in parsing, processing, and analysis using Python, a key language used by engineers.

How to Answer

It’s always best to understand the business use case first to determine the scope of the problem. Then, lay out your solution while clearly stating any assumptions you’ve made.


“I would use the Python json library to parse the file. For large files, I might consider ijson or pandas with read_json, which can handle JSON data in a more memory-efficient manner. I would then use pandas for data processing and aggregation, as well as to filter, clean, or fill in any missing values. For example, missing values could be filled with averages or median values, or I could use more sophisticated imputation techniques depending on the business use case. Additionally, I would implement checks for outliers using functions from Scipy or numpy.”

15. You are given a table CustomerData with columns CustomerID, Name, Email, and SignUpDate. You notice that some of the email addresses are invalid, and some names contain extra whitespace characters. You are asked to write an SQL script to clean these anomalies. Also, explain how you would identify and handle any other potential data quality issues in this table.

In a Microsoft environment, maintaining high data quality is crucial for engineers to facilitate customer relationship management, marketing, and analytics, and this question tests this ability.

How to Answer

Discuss the use of SQL functions for string manipulation and validation. Also, talk about general data quality checks you would perform on the table and how you would rectify identified issues.


“For email validation, I would use a combination of string functions and a regular expression to flag invalid formats. For the names, functions like TRIM can be used to remove extra whitespaces. Beyond these specific issues, I would look for common data quality problems such as null or missing values, duplicates, and inconsistent data entries.”

16. What is the Hadoop Distributed File System (HDFS)? How does it differ from a traditional file system?

Microsoft’s Azure HDInsight service integrates with Hadoop, making knowledge of HDFS crucial for engineers to handle large-scale processing and storage in a distributed computing environment.

How to Answer

Your answer should focus on aspects like scalability, fault tolerance, data distribution, and how HDFS manages large datasets.


“Unlike traditional file systems, HDFS spreads data across many nodes, allowing it to handle petabytes of data. HDFS is highly fault-tolerant; it stores multiple copies of data (replicas) on different machines, ensuring that data is not lost if a node fails. It is designed to work with commodity hardware, making it cost-effective for handling massive amounts of data. HDFS is tightly integrated with the MapReduce programming model, allowing for efficient processing.”

17. How would you implement a binary search algorithm?

Having a good understanding of basic concepts like binary search is imperative. A data engineer at Microsoft will need to use this algorithm a lot of the time to quickly retrieve data from sorted datasets.

How to Answer

Describe the binary search algorithm, emphasizing its efficiency and the conditions under which it operates (e.g., the data must be sorted). Explain the step-by-step process of dividing the search interval in half and how the search space is reduced at each step.


“I would start by identifying the low and high boundaries of the array (or list) containing the data. The algorithm then enters a loop where it calculates the midpoint of the low and high boundaries. If the element at the midpoint is equal to the target value, the search is successful and the index is returned. If the target value is less than the element at the midpoint, the algorithm repeats for the lower half of the array (adjusting the high boundary). If the target value is greater, it repeats for the upper half (adjusting the low boundary). This process continues until the element is found or the low boundary exceeds the high boundary, indicating the element is not in the array. Binary search is efficient with a time complexity of O(log n), making it suitable for large datasets.”

18. Why do you want to join Microsoft?

Microsoft wants to hire individuals who are passionate about what the company stands for. Interviewers will want to know why you specifically chose to apply for the Data Engineer role at Microsoft and whether you have done your research properly.

How to Answer

Your answer should cover why you chose the company and role and why you’re a good match for both. Try to frame your answer positively and honestly. Additionally, focus on the value you’ll bring to the organization.


“I want to work for Microsoft because I am deeply inspired by its commitment to innovation and its role in shaping the future of technology, particularly in cloud computing and AI. The company’s culture of diversity and inclusion aligns with my values.

“I bring a blend of technical proficiency and a passion for data-driven problem-solving. Additionally, my collaborative approach and experience in diverse teams will ensure that I’m a great fit.”

19. Tell me about a time you failed.

As a data engineer, you’ll make mistakes from time to time. In a collaborative culture like Microsoft’s, they’ll want to know if you’re able to be open about mistakes and utilize the learnings to continuously improve and educate.

How to Answer

Familiarize yourself with the STAR (Situation, Task, Action, Result) method to structure your response in an organized manner.

When answering this question, especially in the context of Microsoft’s open and collaborative culture, it’s important to be honest and reflective. Choose a real example of a professional error, describe what happened, and most importantly, what you learned and how it shaped your growth. Emphasize how you took responsibility and how this experience has changed your approach to challenges and teamwork.


“In my previous role, I was tasked with optimizing a complex ETL process that was taking too long to complete. I proposed a series of performance improvements based on my analysis. However, when I implemented them, the process crashed, causing a significant data outage. It was a critical failure, and I had to work tirelessly with the team to resolve the issue.

This experience taught me the importance of thorough testing and monitoring during any system optimization. I also learned the value of communication with the team and stakeholders, keeping them informed of progress and setbacks.”

20. Can you describe a situation where you had to collaborate with a difficult team member?

The interviewer needs to understand how you handle conflicts in a team setting, as data engineering often requires close collaboration with various teams in Microsoft.

How to Answer

Use the STAR method of storytelling - discuss the Specific situation you were challenged with, the Task you decided on, the Action you took, and the Result of your efforts. Make sure to quantify impact when possible.


“In a past project, I worked with a team member who tended to make unilateral decisions and had difficulty effectively communicating their thought process.

Realizing this was affecting our productivity and team dynamics, I requested a private meeting with this colleague. I aimed to understand their perspective while expressing the team’s concerns in a constructive way. During our conversation, I learned that their approach stemmed from a deep sense of responsibility and a fear of project failure. I acknowledged their commitment and then elaborated on how collaborative decision-making could enhance project outcomes.

We agreed on a more collaborative approach, with regular briefings where updates were clearly outlined. This experience taught me the value of addressing interpersonal challenges head-on, but with empathy. The situation improved significantly after our discussion.”

How to Prepare for a Data Engineer Interview at Microsoft

Here are some tips to help you excel in your interview.

Study the Company and Role

Research the role, team, and company.

Research recent news, updates, Microsoft values, and business challenges the company is facing. Understanding the company’s culture and strategic goals will allow you to not only present yourself better but also understand if they are a good fit for you.

Additionally, review the job description carefully. Tailor your preparation to the specific requirements and technologies mentioned in the job description.

You can also read Interview Query members’ experiences on our discussion board for insider tips and first-hand information.

Brush Up on Technical Skills

Make sure you have a strong foundation in programming languages like Python, Java, and Scala, as well as SQL and data structures. Familiarity with cloud computing platforms like Azure is also a plus.

Check out the resources we’ve tailored for data engineers: a case study guide, a compendium of data engineer interview questions, data engineering projects to add to your resume, and a list of great books to help you on your engineering journey. If you need further guidance, you can consider our tailored data engineering learning path as well.

Prepare Behavioral Interview Answers

Soft skills such as collaboration, effective communication, and problem-solving are paramount to succeeding in any job, especially in a collaborative culture such as Microsoft’s.

To test your current preparedness for the interview process, try a mock interview to improve your communication skills.

Keep Up With The Industry

The data engineering landscape is constantly evolving, so keep yourself updated on the latest technologies, news, and best practices.

Network With Employees

Connect with people who work at Microsoft through LinkedIn or other online platforms. They can provide valuable insights into the company culture and the interview process.

Consider checking our complete Data Engineer Prep Guide to make sure that you don’t miss anything important while preparing for your interview at Microsoft.


What is the average salary for a Data Engineer role at Microsoft?


Average Base Salary


Average Total Compensation

Min: $79K
Max: $160K
Base Salary
Median: $137K
Mean (Average): $131K
Data points: 15
Min: $32K
Max: $212K
Total Compensation
Median: $165K
Mean (Average): $157K
Data points: 15

View the full Data Engineer at Microsoft salary guide

The average base salary for a Data Engineer at Microsoft is $135,221, making the remuneration considerably higher than that of the average data engineering role in the US.

For more insights into the salary range of a data engineer at various companies, segmented by city, seniority, and company, check out our comprehensive Data Engineer Salary Guide.

Where can I read more discussion posts on the Microsoft Data Engineer role here on Interview Query?

Here is our discussion board, where our members talk about their Microsoft interview experience. You can also use the search bar to look up data engineer interview experiences in other firms to gain more insight into interview patterns.

Are there job postings for Microsoft Data Engineer roles on Interview Query?

We have jobs listed for data engineer roles in Microsoft, which you can apply for directly through our job portal. You can also have a look at similar roles that are relevant to your career goals and skill set.


In conclusion, succeeding in a Microsoft Data Engineer interview requires not only a strong foundation in technical skills and problem-solving but also the ability to work in a collaborative environment.

If you’re considering opportunities at other tech companies, check out our Company Interview Guides. We cover a range of companies, including GoogleIBM, Apple, and more.

For other data-related roles at Microsoft, consider exploring our guides for Business AnalystData AnalystScientist, and Software Engineer positions in our main Microsoft interview guide.

If you’re looking for a broader set of information about interview questions for data engineers, then you can look through our main data engineering interview guide, case studies, as well as our Python and SQL sections.

Understanding Microsoft’s culture of innovation and collaboration and preparing thoroughly with both technical and behavioral questions is the key to your success.

Check out more of Interview Query’s content, and we hope you’ll land your dream role at Microsoft very soon!