Coupang is one of the fastest-growing e-commerce companies and a dominant force in South Korean commerce. Born out of a mission to make shopping, eating, and living easier, we are redefining the industry with our innovative approach. Our startup culture, backed by the resources of a global company, allows us to launch new services rapidly and empower bold, ambitious individuals to make a hands-on impact.

Data Engineer Position Overview

At Coupang, the Data Engineer role is critical in designing, developing, and maintaining our data architectures, including data lakes, warehouses, and pipelines. As a Data Engineer, you will work across various business domains to understand data needs, build reliable data products, and enable data-driven decision-making.

Skills Required

• Strong programming skills in languages like Python, Scala, and Java.
• Expertise in distributed processing technologies (e.g., Spark, Hive).
• Hands-on experience with data warehousing and database systems (SQL, NoSQL).
• Familiarity with cloud platforms such as AWS.
• Ability to design scalable data architectures and pipelines.
• Problem-solving skills and a pragmatic approach to technical challenges.

What We Look For

Coupang is seeking individuals who are technically adept, collaborative, and passionate about driving innovation. The ideal candidate will possess strong analytical skills, the ability to manage large-scale data projects, and an interest in pushing the boundaries of e-commerce technology.

At Interview Query, we’re dedicated to helping you navigate the Data Engineer hiring process at Coupang. This guide will provide you with insider tips and recurring questions to bolster your prep and increase your chances of landing the role. Dive in to learn how to successfully crack the Coupang interview!

Typically, interviews at Coupang vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

Submitting Your Application

The first step in joining Coupang as a Data Engineer is to submit an application that effectively showcases your technical skills and genuine interest in the role. If you were contacted by a Coupang recruiter or took the initiative to apply yourself, thoroughly review the job description and tailor your resume to match the job requirements.

Include relevant keywords and skills that the hiring manager might look for and craft a targeted cover letter that highlights your experience with data systems, SQL, and big data technologies. Emphasize any projects or roles where you have demonstrated problem-solving, data design, and warehousing skills.

Recruiter/Hiring Manager Call Screening

Upon shortlisting, a recruiter from Coupang's Talent Acquisition Team will contact you to verify your experience, skill level, and interest in the role. During this call, expect behavioral questions and preliminary technical discussions.

Sometimes, the hiring manager may also join the call to answer your queries about the team and the overall role at Coupang. This initial screening usually takes about 30 minutes.

Technical Coding Test

If you pass the initial screening, you will be invited to complete a coding test. This is typically done using online platforms like HackerRank and will assess your problem-solving skills, coding proficiency, and familiarity with algorithms and data structures.

Technical Virtual Interview

Successfully navigating the coding test will lead to a technical virtual interview. This virtual stage, usually 1-1.5 hours long, involves solving algorithmic problems, often via platforms like HackerRank, and potential discussions on SQL queries or database management. You may be asked questions related to parsing intervals, tree traversal, and other common data engineering problems.

Depending on the role, additional areas such as system design, multithreading, and data structure efficiency may also be evaluated.

Onsite Interview Rounds

After clearing the virtual technical round, you'll be invited for onsite interview rounds, which generally include:

1. Technical Rounds: These sessions will focus heavily on problem-solving, coding, system design, and technical knowledge. Typical formats include coding on a whiteboard, discussing system design, and explaining algorithms.
2. Behavioral Interviews: Discussion around your past experiences, challenges you faced, and how you embody Coupang’s core values.
3. Case Study/Business Questions: For senior roles, you might be asked to explain how you’d solve specific business problems or justify your approach to various scenarios.

Organizing these rounds can sometimes be inconsistent, so patience is key.

Final HR Interview

The concluding step is an HR interview, where you will discuss expectations, company culture, compensation, and any final questions you may have. This is also a great time to gauge if Coupang is the right fit for you.

Quick Tips For Coupang Data Engineer Interviews

• Technical Proficiency: Ensure you’re comfortable with data algorithms, multithreading, and SQL. Practice coding problems on platforms like HackerRank and LeetCode.
• Prepare for System Design: Be ready to design systems and databases, as this is a significant part of the interview process, particularly for senior roles.
• Understand Coupang's Culture and Products: Be prepared to discuss how your own values align with Coupang’s mission and culture. Research their products and recent developments to add context to your answers.

Practice for the Coupang Data Engineer interview with these recently asked interview questions.

Coupang Data Engineer Coding and Algorithms Interview Questions

Coding and algorithms questions are present in 82% of Coupang job interviews. They are particularly common in data scientist (97%), machine learning engineer (97%), and software engineer (97%) interviews.

1 - Write a function to find the nearest common ancestor of two nodes in a binary tree. You are given a binary tree of unique positive numbers. Each node in the tree is implemented as a dictionary with the keys left and right, indicating the node's left and right neighbors, respectively, and data that holds an integer value. Given two nodes as input (value1 and value2), write a function to return the value of the nearest node that is a parent to both nodes. If one of the nodes doesn't exist in the tree, return -1.

2 - Create a function to reconstruct the path of a trip from unordered flight tickets. Consider a trip from one city to another that may contain many layovers. Given the list of flights out of order, each with a starting city and end city, write a function plan_trip to reconstruct the path of the trip so the trip tickets are in order.

3 - Write a function to compute the minimum number of parking spots needed for buses. Given a list of tuples, each containing two integers representing the arrival and departure time of buses, write a function minimum_parking_spots that computes the minimum number of parking spots needed to accommodate all the buses. The arrival and departure times are given in hours, ranging from 0 (12:00 AM) to 24 (11:59 PM). A bus only leaves on the next hour after its arrival.

4 - Write a SQL query to calculate the 3-day weighted moving average of sales for each product. The sales department is conducting a performance review and is interested in trends in product sales. Write a SQL query to calculate the 3-day weighted moving average of sales for each product. Use the weights 0.5 for the current day, 0.3 for the previous day, and 0.2 for the day before that. Only output the weighted moving average for dates that have two or more preceding dates.

To practice Algorithms interview questions, consider using the Python learning path or the full list of Algorithms questions in our database.

Coupang Data Engineer Analytics and Experiments Interview Questions

Analytics and Experiments questions appear in 72% of Coupang job interviews. They are most frequently asked during data analyst (97%), business analyst (19%), and software engineer (13%) interviews.

1 - How would you set up an A/B test for button color and position changes in a sign-up funnel? A team wants to A/B test multiple changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you set up this test?

2 - How could you promote Instagram through Facebook? You work on the growth team at Facebook and are tasked with promoting Instagram from within the Facebook app. Where and how could you promote Instagram through Facebook?

3 - What metrics, graphs, or models would you use to analyze churn behavior for different pricing plans? You work for a company like Netflix, which has two pricing plans: $15/month or $100/year. An executive wants you to analyze the churn behavior of users subscribed to either plan. What kinds of metrics, graphs, or models would you build to provide an overarching view of subscription performance?

4 - What analysis would you run for an A/B test with non-normal distribution at Uber Fleet? Uber Fleet has low data for experimentation, and you find that the distribution is not normal in an A/B test. What kind of analysis would you run, and how would you measure which variant won?

5 - What retention rate is required to surpass revenue from a non-subscription price? You sell an e-commerce product for $29 with a 50% per unit margin. You want to switch to a monthly subscription model at a 20% discount on the retail price. What retention rate would be required to surpass the revenue from the non-subscription price?

To prepare for analytics and experiments, consider using the product metrics learning path and the data analytics learning path.

Coupang Data Engineer Machine Learning Interview Questions

Machine learning questions appear in 10% of Coupang job interviews. There are no specific positions for which these questions are most frequent.

1 - What metrics would you use to track the accuracy and validity of a spam classifier model? Assume you have built a V1 of a spam classifier for emails. What metrics would you use to evaluate its accuracy and validity?

2 - When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. In which scenarios would you prefer a bagging algorithm over a boosting algorithm? Provide examples of the tradeoffs between the two.

3 - What are the assumptions of linear regression? List and explain the assumptions that must be met for linear regression to be valid.

4 - How would you build a restaurant recommender on Facebook? Describe how you would gather data and build a restaurant recommender system on Facebook. What are some potential downfalls or concerns with adding this feature?

5 - How would you design the YouTube video recommendation algorithm? Explain how you would design a recommendation system for YouTube videos. What important factors should be considered when building this algorithm?

To get ready for machine learning interview questions, we recommend taking the machine learning course.

Coupang Data Engineer Statistics and Probability Interview Questions

Statistics and probability questions do not come up in Coupang job interviews. There are no specific positions where these types of questions are asked.

1 - How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to a non-technical person, focusing on its role in determining the significance of results in hypothesis testing.

2 - What could be the cause of the decrease in overall capital approval rates? Analyze why the overall capital approval rate dropped from 85% to 82% despite individual product approval rates staying flat or increasing. Consider potential factors such as changes in the mix of products or external influences.

3 - What is the probability that both flips result in the same side with one fair and one biased coin? Calculate the probability that two flips of a randomly selected coin (one fair, one biased with 3/4 heads) result in the same side.

4 - What is the percentage chance a review is actually fake when the algorithm detects it as fake? Given that 98% of reviews are legitimate and 2% are fake, and the algorithm's accuracy rates, calculate the probability that a review is fake when identified as fake by the algorithm.

5 - What kind of analysis would you run for non-normal distribution in an AB test with low data at Uber Fleet? Determine the appropriate analysis method for an AB test with non-normal distribution and low data volume at Uber Fleet. Explain how you would measure which variant won.

To prepare for statistics and probability interview questions, consider using the A/B testing and statistics learning path and the comprehensive probability learning path.