GlobalLogic Data Engineer Interview Questions + Guide in 2024

GlobalLogic is a leader in digital engineering, helping brands design and build innovative products, platforms, and experiences. By blending design, engineering, and data expertise, GlobalLogic drives digital transformation for clients in industries such as automotive, healthcare, finance, and technology.

As a Hitachi Group Company, GlobalLogic focuses on sustainability through tech innovation. Headquartered in Silicon Valley, with engineering centers worldwide, the company’s global reach enables them to solve complex industry challenges.

If you’re aiming for a Data Engineer role at GlobalLogic, expect interview questions that test your proficiency in big data technologies like Apache Spark, experience with ETL processes, and experience with cloud platforms such as Azure. The role involves designing scalable data pipelines, optimizing system performance, and working closely with stakeholders to deliver impactful data solutions.

This guide will explore GlobalLogic data engineer interview questions to help you prepare and succeed in landing a role at this cutting-edge firm at the forefront of digital transformation.

The interview process usually depends on the role and seniority; however, you can expect the following on a GlobalLogic data engineer interview:

Recruiter/Hiring Manager Call Screening

If your CV catches the eye of the hiring team, a recruiter from GlobalLogic will contact you to verify key details such as your background, project work, work authorization, and readiness to relocate. This call might include behavioral questions and a brief chat about the role and salary expectations.

This introductory call will usually last about 30 minutes.

Technical Virtual Interview

Successfully passing the initial screening will lead to a technical interview. This interview is generally conducted through videoconferencing and requires screen sharing. During this one-hour session, expect to discuss your project experiences in detail and answer questions about specific technologies like Python, data frame, numpy, pandas, ETL processes, SQL queries, etc.

The interview may delve deeply into the projects you’ve completed, asking why and how you used a specific technology and how you could potentially improve that solution. You might also face coding challenges related to Python or other relevant technical areas.

Onsite Interview Rounds

After surviving the technical virtual interview, you will be invited for on-site interview rounds. This stage may consist of multiple rounds focusing on different aspects—technical skills, project management, and potential fit within the company. Expect questions on programming languages (Scala, Python, etc.), data engineering (Spark, Hadoop, etc.), and soft skills like teamwork and problem-solving abilities.

Good luck with your interview journey at GlobalLogic!

Typically, interviews at GlobalLogic vary by role and team, but commonly, data engineer interviews follow a fairly standardized process across these question topics.

1. Given two strings, string1 and string2, write a function str_map to determine if there exists a one-to-one correspondence (bijection) between the characters of string1 and string2.

For the two strings, our correspondence must be between characters in the same position/index.

Example 1:

Input:

string1 = 'qwe'
string2 = 'asd'

string_map(string1, string2) == True

# q = a, w = s, and e = d

Example 2:

Input:

string1 = 'donut'
string2 = 'fatty'

string_map(string1, string2) == False
# cannot map two distinct characters to two equal characters

Example 3:

Input:

string1 = 'enemy'
string2 = 'enemy'

string_map(string1, string2) == True
# there exists a one-to-one correspondence between equivalent strings

Example 4:

Input:

string1 = 'enemy'
string2 = 'ymene'

string_map(string1, string2) == False
# since our correspondence must be between characters of the same index, this case returns 'False' as we must map e = y AND e = e

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

Explain how a random forest generates multiple decision trees to form a forest. Discuss the advantages of using random forest over logistic regression, such as handling non-linear data and reducing overfitting.

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

Compare two machine learning algorithms and describe scenarios where bagging is preferred over boosting. Provide examples of the tradeoffs, such as variance reduction in bagging and bias reduction in boosting.

4. How would you evaluate and compare two credit risk models for personal loans?

1. Identify the type of model developed by the co-worker for loan approval.
2. Describe how to measure the difference between two credit risk models over a timeframe, considering monthly installment payments.
3. List the metrics to track for measuring the new model’s success, such as accuracy, precision, recall, and AUC-ROC.

5. What’s the difference between Lasso and Ridge Regression?

Explain the key differences between Lasso and Ridge Regression, focusing on their regularization techniques and how they handle feature selection and multicollinearity.

6. What are the key differences between classification and regression models?

Describe the main differences between classification and regression models, including their objectives, output types, and common use cases.

7. How would you design a function to detect anomalies in univariate and bivariate datasets?

How would you design a function to detect anomalies if given a univariate dataset? What if the data is bivariate?

8. What are the drawbacks of the given student test score data layouts, and how would you reformat them?

Assume you have data on student test scores in two layouts (dataset 1 and dataset 2). Identify the drawbacks of these layouts, suggest formatting changes for better analysis, and describe common problems in “messy” datasets.

9. What is the expected churn rate in March for customers who bought a subscription since January 1st?

You noticed that 10% of customers who bought subscriptions in January 2020 canceled before February 1st. Assuming uniform new customer acquisition and a 20% month-over-month decrease in churn, calculate the expected churn rate in March for all customers who bought the product since January 1st.

10. How would you explain a p-value to a non-technical person?

Describe what a p-value is in simple terms for someone who is not familiar with technical or statistical concepts.

11. What are Z and t-tests, and when should you use each?

Explain Z and t-tests, their uses, their differences, and when to use one over the other.

12. What metrics would you use to determine the value of each marketing channel?

Given marketing channels and their costs for a B2B analytics dashboard company, identify key metrics to evaluate each channel’s value.

13. How would you determine the next partner card using customer spending data?

Using customer spending data, outline a method to identify the best partner for a new credit card offering.

14. How would you investigate if the redesigned email campaign led to the increase in conversion rate?

Analyze the impact of a redesigned email campaign on conversion rates. Determine if the increase is due to the campaign or other factors.

Here are a few tips to help you excel in the GlobalLogic software engineer interview process:

1. Brush Up on Your Technical Skills: Ensure you’re well-versed with the technologies listed in the job descriptions, such as Apache Spark, Scala, ETL processes, and SQL. Practicing coding challenges and reviewing data engineering fundamentals can be beneficial.

2. Understand Your Projects Thoroughly: Be prepared to discuss your past projects in-depth. You should be able to explain why you chose specific technologies, the challenges faced, and how you overcame them.

3. Effective Communication: Clear and concise communication is key. Make sure to articulate your thoughts well. Being able to explain complex technical concepts thoroughly is a valuable skill.

What is the average salary for a Data Engineer at GlobalLogic?

According to Glassdoor, GlobalLogic’s data engineers earn between $90K and $122K per year, with an average of $105K per year.

What does GlobalLogic offer to Data Engineers?

GlobalLogic offers exciting projects at the forefront of digital transformation, a collaborative environment with a diverse team, excellent work-life balance with flexible schedules, professional development through continuing education and certification, and competitive benefits, including health and life insurance, 401K plans, and PTO.

What skills are required for a Data Engineer position at GlobalLogic?

Candidates should possess expertise in Apache Spark, Scala, and Java, with strong programming skills in languages like Python. A solid understanding of big data technologies, ETL processes, and data warehousing principles is essential. Experience with cloud platforms like AWS or Azure, and familiarity with SQL and NoSQL databases, is also highly desirable.

What kinds of projects do Data Engineers work on at GlobalLogic?

Data Engineers at GlobalLogic work on innovative, market-defining products and digital experiences across various industries, including automotive, healthcare, financial services, and media. Projects range from building big data infrastructures and data pipelines to integrating machine learning and AI technologies into client solutions.

How does GlobalLogic support career development for Data Engineers?

GlobalLogic promotes professional growth through continuing education classes, technical and soft skills training, and professional certifications. Employees benefit from knowledge exchanges within the global organization, attending workshops, and collaborating with experts from different fields.

GlobalLogic offers a collaborative environment, exciting projects, and a strong commitment to work-life balance, making it an ideal workplace for those passionate about technology and innovation.

By joining the team, you’ll benefit from professional development opportunities, international exchanges, and excellent benefits — positioning you at the cutting edge of the digital transformation landscape.

To explore more interview guides from this company, visit the GlobalLogic main interview guide here at Interview Query.

Good luck with your interview!