Udemy Data Engineer Interview Questions + Guide in 2025

At Udemy, we’re on a mission to improve lives through the power of learning, serving as one of the world’s largest education platforms with over 57 million learners.

As a Data Engineer at Udemy, you will play a critical role in developing and maintaining the data architecture that supports the company’s mission of making learning accessible and effective for everyone. Your key responsibilities will include designing and implementing data systems, ensuring the quality and scalability of data processes, and collaborating with cross-functional teams to define data flows between various platforms. You will utilize your expertise in SQL and Python to create efficient data pipelines, support data analytics initiatives, and enhance the overall data engineering culture within the organization. The ideal candidate will possess deep knowledge of the modern data stack, including ETL processes, real-time data streaming, and cloud services, and will thrive in a collaborative, innovative environment.

This guide will help you prepare for your interview by providing insights into the expectations for the role and the skills you need to emphasize during your discussions with the interviewers.

The interview process for a Data Engineer position at Udemy is structured to assess both technical skills and cultural fit within the organization. It typically consists of several stages, each designed to evaluate different aspects of a candidate's qualifications and compatibility with Udemy's mission and values.

1. Initial Phone Screen

The process begins with a 30-minute phone interview conducted by a recruiter. This initial screen focuses on understanding your background, experiences, and motivations for applying to Udemy. Expect to discuss your technical skills, particularly in SQL and Python, as well as your familiarity with data engineering concepts. The recruiter will also gauge your alignment with Udemy's culture and values.

2. Technical Assessment

Following the initial screen, candidates are usually required to complete a technical assessment, often through a platform like HackerRank. This assessment typically includes a mix of coding challenges that test your problem-solving abilities, particularly in algorithms and data structures. You may encounter questions related to SQL queries, data manipulation, and possibly some open-ended design questions that assess your understanding of data architecture.

3. Technical Interview

Candidates who perform well in the technical assessment will move on to a more in-depth technical interview, which may be conducted via video call. This interview usually lasts between 45 minutes to an hour and involves discussions with senior engineers or hiring managers. Expect to tackle questions that cover your experience with data engineering tools and frameworks, such as ETL processes, data modeling, and cloud services. You may also be asked to solve coding problems in real-time, demonstrating your thought process and coding proficiency.

4. Onsite Interview

The final stage of the interview process is an onsite interview, which can last several hours and typically consists of multiple rounds. Candidates may face three to five interviews, each focusing on different areas such as system design, data architecture, and behavioral questions. During this stage, you will likely engage in discussions about your past projects, how you approach problem-solving, and your ability to collaborate with cross-functional teams. The onsite interview may also include a lunch session with team members to assess cultural fit in a more informal setting.

Throughout the interview process, Udemy emphasizes the importance of communication skills and the ability to work collaboratively, so be prepared to discuss how you have successfully navigated team dynamics in your previous roles.

As you prepare for your interview, consider the types of questions that may arise in each of these stages, particularly those that align with the skills and experiences outlined in the job description.

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

Understand the Interview Structure

The interview process at Udemy typically includes a recruiter phone screen, followed by a technical interview that may involve coding challenges, and an onsite interview with multiple rounds focusing on both technical and behavioral aspects. Familiarize yourself with this structure and prepare accordingly. Knowing what to expect can help you manage your time and energy effectively during the interview.

Master Key Technical Skills

Given the emphasis on SQL and algorithms in the role, ensure you are well-versed in these areas. Practice SQL queries, focusing on complex joins, window functions, and data manipulation. Additionally, brush up on algorithmic problem-solving, particularly graph-based problems and data structures. Utilize platforms like LeetCode or HackerRank to simulate the coding challenges you may face.

Prepare for Behavioral Questions

Udemy values collaboration and cultural fit, so be ready to discuss your past experiences in team settings. Reflect on situations where you demonstrated problem-solving skills, adaptability, and leadership. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey your thought process and the impact of your actions.

Showcase Your Passion for Learning

As a company dedicated to education, Udemy appreciates candidates who are enthusiastic about continuous learning. Be prepared to discuss how you stay updated with industry trends and technologies. Mention any relevant courses you’ve taken on Udemy or other platforms, and express your commitment to personal and professional growth.

Emphasize Collaboration and Communication

The role requires working closely with cross-functional teams, so highlight your ability to communicate complex technical concepts to non-technical stakeholders. Share examples of how you’ve successfully collaborated with others to achieve common goals. This will demonstrate your fit within Udemy’s team-oriented culture.

Be Ready for Technical Challenges

Expect to face technical challenges that test your problem-solving abilities. During coding interviews, think aloud to show your reasoning and approach. If you encounter a difficult problem, don’t hesitate to ask clarifying questions or discuss your thought process. Interviewers appreciate candidates who can articulate their thinking, even if they don’t arrive at the correct solution.

Stay Positive and Professional

Throughout the interview process, maintain a positive attitude, even if you encounter setbacks or delays. Udemy values integrity and professionalism, so be respectful and courteous to everyone you interact with, from recruiters to interviewers. This will leave a lasting impression and reflect well on your candidacy.

Follow Up Thoughtfully

After your interviews, send a thank-you email to express your appreciation for the opportunity to interview. Use this as a chance to reiterate your enthusiasm for the role and the company. A thoughtful follow-up can set you apart from other candidates and reinforce your interest in joining Udemy.

By preparing thoroughly and aligning your approach with Udemy's values and expectations, you can enhance your chances of success in the interview process. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Udemy. The interview process will likely cover a range of topics, including SQL, algorithms, Python coding, and behavioral aspects. Candidates should be prepared to demonstrate their technical skills as well as their ability to work collaboratively in a team environment.

SQL and Database Management

1. How would you optimize a slow SQL query?

Understanding query optimization is crucial for a Data Engineer, as performance can significantly impact data processing tasks.

How to Answer

Discuss specific techniques such as indexing, query rewriting, and analyzing execution plans. Mention any tools you have used to identify bottlenecks.

Example

"I would start by analyzing the execution plan to identify any slow operations. If I find that certain columns are frequently filtered or joined, I would consider adding indexes. Additionally, I would look for opportunities to rewrite the query to reduce complexity, such as using joins instead of subqueries."

2. Can you explain the difference between INNER JOIN and LEFT JOIN?

This question tests your understanding of SQL joins, which are fundamental in data manipulation.

How to Answer

Clearly define both types of joins and provide examples of when each would be used.

Example

"An INNER JOIN returns only the rows where there is a match in both tables, while a LEFT JOIN returns all rows from the left table and the matched rows from the right table. For instance, if I want to list all customers and their orders, I would use a LEFT JOIN to ensure I include customers who haven't placed any orders."

3. What are window functions in SQL, and when would you use them?

Window functions are essential for performing calculations across a set of table rows related to the current row.

How to Answer

Explain what window functions are and provide a scenario where they would be beneficial.

Example

"Window functions allow you to perform calculations across a set of rows related to the current row without collapsing the result set. For example, I would use a window function to calculate a running total of sales over time while still displaying each individual sale."

4. Describe a time you had to design a database schema. What factors did you consider?

This question assesses your practical experience in database design.

How to Answer

Discuss the principles of normalization, data types, and relationships between tables that you considered in your design.

Example

"When designing a database for an e-commerce platform, I focused on normalization to reduce redundancy. I created separate tables for users, products, and orders, ensuring that foreign keys maintained relationships. I also considered indexing frequently queried columns to improve performance."

Algorithms and Data Structures

1. How would you find the shortest path in a graph?

This question tests your knowledge of graph algorithms, which are often used in data engineering tasks.

How to Answer

Mention specific algorithms like Dijkstra's or A* and explain the scenarios in which you would use them.

Example

"I would use Dijkstra's algorithm to find the shortest path in a weighted graph. It works well for graphs with non-negative weights, and I would implement it using a priority queue to efficiently select the next node to process."

2. Can you explain the concept of Big O notation? Why is it important?

Understanding algorithm efficiency is crucial for a Data Engineer.

How to Answer

Define Big O notation and discuss its significance in evaluating algorithm performance.

Example

"Big O notation describes the upper limit of an algorithm's running time as the input size grows. It's important because it helps us understand how an algorithm will scale and allows us to compare the efficiency of different algorithms."

3. Describe a time you had to implement a data structure from scratch. What challenges did you face?

This question assesses your practical coding skills and problem-solving abilities.

How to Answer

Discuss the data structure you implemented, the challenges you encountered, and how you overcame them.

Example

"I implemented a custom hash table to optimize data retrieval. One challenge was handling collisions, which I resolved by implementing separate chaining. This experience taught me the importance of balancing efficiency with memory usage."

4. How would you merge two sorted arrays?

This question tests your understanding of algorithms and array manipulation.

How to Answer

Explain the approach you would take to merge the arrays efficiently.

Example

"I would use a two-pointer technique to iterate through both arrays simultaneously, comparing the current elements and adding the smaller one to the result array. This approach ensures that the merge operation runs in linear time, O(n)."

Python and Coding Skills

1. How do you handle exceptions in Python?

This question assesses your knowledge of error handling in Python.

How to Answer

Discuss the use of try-except blocks and any best practices you follow.

Example

"I use try-except blocks to handle exceptions in Python. I ensure to catch specific exceptions rather than using a general exception to avoid masking other issues. Additionally, I always log the error details for debugging purposes."

2. Can you explain the difference between a list and a tuple in Python?

This question tests your understanding of Python data structures.

How to Answer

Clearly define the differences in mutability and use cases for each.

Example

"A list is mutable, meaning it can be changed after creation, while a tuple is immutable. I typically use lists for collections of items that may change, and tuples for fixed collections of items, such as coordinates."

3. Write a Python function to reverse a string.

This question tests your coding skills and understanding of string manipulation.

How to Answer

Provide a clear and efficient solution to the problem.

Example

"To reverse a string in Python, I would use slicing: def reverse_string(s): return s[::-1]. This approach is concise and leverages Python's built-in capabilities."

4. How would you implement a basic RESTful API in Python?

This question assesses your knowledge of web services and API design.

How to Answer

Discuss the frameworks you would use and the key components of a RESTful API.

Example

"I would use Flask to implement a basic RESTful API in Python. I would define routes for different endpoints, handle HTTP methods like GET and POST, and return JSON responses. Additionally, I would ensure to implement proper error handling and validation."

Behavioral Questions

1. Describe a challenging project you worked on. What was your role?

This question assesses your teamwork and problem-solving skills.

How to Answer

Discuss the project, your specific contributions, and the outcome.

Example

"I worked on a data migration project where I was responsible for designing the ETL process. The challenge was ensuring data integrity during the migration. I collaborated closely with the data quality team to implement validation checks, which ultimately led to a successful migration with minimal issues."

2. How do you prioritize your tasks when working on multiple projects?

This question evaluates your time management and organizational skills.

How to Answer

Discuss your approach to prioritization and any tools you use.

Example

"I prioritize tasks based on their impact and deadlines. I use project management tools like Trello to visualize my workload and ensure I'm focusing on high-priority tasks first. Regular check-ins with my team also help me stay aligned with project goals."

3. How do you handle conflicts within a team?

This question assesses your interpersonal skills and conflict resolution strategies.

How to Answer

Discuss your approach to addressing conflicts and maintaining a positive team dynamic.

Example

"When conflicts arise, I believe in addressing them directly and respectfully. I encourage open communication and try to understand each person's perspective. By facilitating a discussion, we can often find common ground and move forward collaboratively."

4. Why do you want to work at Udemy?

This question gauges your motivation and alignment with the company's mission.

How to Answer

Express your enthusiasm for Udemy's mission and how your values align with the company.

Example

"I admire Udemy's commitment to making education accessible to everyone. As a Data Engineer, I want to contribute to a platform that empowers learners worldwide. I believe my skills can help enhance the data systems that support this mission."