EPAM Systems Data Engineer Interview Questions + Guide in 2024

EPAM Systems is a leading global provider of digital platform engineering and development services. Known for its innovative and dynamic approach, EPAM partners with top companies worldwide to deliver cutting-edge technological solutions. Driven by a diverse, creative, and inclusive culture, EPAM encourages its employees to collaborate and grow, offering continuous learning and development opportunities.

In this guide, we’ll walk you through the interview process, provide insights into commonly asked EPAM Systems data engineer interview questions, and offer some valuable tips to help you succeed. Let’s get started!

The interview process usually depends on the role and seniority. However, you can expect the following on an EPAM Systems data engineer interview:

Recruiter/Hiring Manager Call Screening

If your CV is among the shortlisted few, a recruiter from the Epam Systems Talent Acquisition Team will contact you and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.

Sometimes, the Epam Systems data engineer hiring manager may also be present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will invite you to the technical screening round. Technical screening for the Epam Systems data engineer role is usually conducted virtually, including video conference and screen sharing. This 1-hour long interview stage may revolve around topics such as:

• Data Warehousing concepts: DWH, Data Lake, Lakehouse
• Cloud experience and cloud services
• Fact vs. Dimensional tables, Star vs. Snowflake schema
• OLAP vs OLTP systems
• Database indexing, NoSQL vs SQL databases
• Spark components and architecture: narrow vs broad transformations
• Python-specific topics like decorators, generators, and profiling tools

Additionally, you may be asked to solve SQL questions involving window functions, essential WHERE clauses, and UNION operations, as well as Python coding tasks like finding max/min values in dictionaries and filtering unique numbers in lists while retaining order.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. The onsite interview usually includes multiple interview rounds conducted by technical and managerial staff. Here’s what you can typically expect:

• Technical Round 1: Questions on big data technologies, ETL processes, and real-world scenario problem-solving using technologies like Scala, Java, or Python.
• Technical Round 2: Hands-on coding challenges involving distributed computing principles, data source integration, and large-scale data frameworks such as Spark, Hadoop, and Hive.
• Manager Round: This round involves an Assessment of your overall experience and fit for the team, involving more situational judgment questions. Salary negotiation and offer details might also be covered.

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

1. Write a SQL query to select the 2nd highest salary in the engineering department.

Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

2. Write a function to merge two sorted lists into one sorted list.

Given two sorted lists, write a function to merge them into one sorted list. Bonus: What’s the time complexity?

3. Write a function missing_number to find the missing number in an array.

You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

4. Write a function precision_recall to calculate precision and recall metrics from a 2-D matrix.

Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

5. Write a function to search for a target value in a rotated sorted array.

Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. You are given a target value to search. If the value is in the array, then return its index; otherwise, return -1.

6. How do you determine the best strategy to increase TikTok’s daily active users (DAU)?

TikTok aims to increase DAU next quarter. Three executives propose different strategies: improving the recommendation algorithm, acquiring new users, and enhancing creator tools. The engineering team must prioritize one feature. How do you determine which strategy is best, and what data points and metrics would help validate your choice?

7. How would you evaluate whether using a decision tree algorithm is the correct model for predicting loan repayment?

You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate if a decision tree is the right choice, and how would you assess its performance before and after deployment?

8. How does random forest generate the forest and why use it over logistic regression?

Explain the process by which a random forest generates its ensemble of trees. Additionally, discuss why one might choose random forest over logistic regression for certain problems.

9. When would you use a bagging algorithm versus a boosting algorithm?

Compare two machine learning algorithms. Describe scenarios where you would prefer a bagging algorithm over a boosting algorithm, and discuss the tradeoffs between the two.

10. How would you justify using a neural network for a business problem and explain its predictions to non-technical stakeholders?

Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

11. What metrics would you use to track the accuracy and validity of a spam classifier?

You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to evaluate the model’s accuracy and validity?

12. Is this a fair coin?

You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

13. How do you write a function to calculate sample variance?

Write a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. For example, given test_list = [6, 7, 3, 9, 10, 15], the function should return 13.89.

14. Is there anything suspicious about the A/B test results?

Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

15. How do you find the median in O(1) time and space?

Given a list of sorted integers where more than 50% of the list is the same repeating integer, write a function to return the median value in O(1) computational time and space. For example, given li = [1, 2, 2], the function should return 2.

16. What are the drawbacks and common problems in messy datasets?

Assume you have data on student test scores in two different layouts (dataset 1 and dataset 2). Identify the drawbacks of these layouts, suggest formatting changes to make the data more useful for analysis, and describe common problems seen in messy datasets.

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your EPAM Systems data engineer interview include:

• Deep Dive Into Big Data Tools: Be prepared to discuss and demonstrate your knowledge of various big data tools and frameworks, such as Spark, Hadoop, Kafka, and Hive. Technical interviewers at Epam Systems are likely to drill deep into these areas.
• Cloud Expertise: Epam Systems often works on cloud-based projects, so make sure you are comfortable with cloud data services, particularly those on AWS, Google Cloud, or Azure.
• Understand DB Performance Optimization: Have a good grasp of database concepts such as indexing, OLAP vs OLTP, materialized views vs regular views, and how to optimize query performance.

What is the average salary for a Data Engineer at Epam Systems?

What technical skills are essential for a Data Engineer at EPAM Systems?

Essential technical skills include proficiency in Scala, Java, or Python, knowledge of distributed computing principles, experience with HDFS, Hive, and Impala, familiarity with ETL processes, and experience in building stream-processing systems using tools like Spark-Streaming. Familiarity with cloud services and messaging systems such as Kafka is also beneficial.

What is the work environment like at EPAM Systems?

EPAM Systems fosters a dynamic and inclusive culture. Team collaboration, innovative projects, and continuous learning opportunities are at the core of EPAM’s work environment. Employees are part of a diverse community that supports personal and professional growth.

What benefits does EPAM Systems offer to its employees?

EPAM Systems offers a comprehensive benefits package, including medical, dental, and vision insurance, health savings account, life and AD&D insurance, employee assistance program, matched 401(k) retirement savings plan, paid time off, and various other perks such as employee discounts and pet insurance.

If you’re aiming to advance your career as a Data Engineer at EPAM Systems, you’re in for a rewarding and challenging journey. The interview process at EPAM is extensive and thorough, covering key areas such as data warehousing, Python, and SQL fundamentals. You’ll encounter diverse questions ranging from DWH concepts and cloud experiences to more specific technical inquiries around OLAP vs. OLTP, fact vs. dimension tables, and even some hands-on coding tasks in Python and SQL.

To get a more in-depth view of what to expect and to prepare effectively, explore our dedicated EPAM Systems Interview Guide, packed with detailed insights and potential interview questions.

Good luck with your interview!