Globallogic Data Engineer Interview Questions + Guide 2024

Introduction to Globallogic for Data Engineer Position

GlobalLogic is a leader in digital engineering, helping brands worldwide design and build innovative products, platforms, and digital experiences. By integrating experience design, complex engineering, and data expertise, GlobalLogic enables clients to envision new possibilities and accelerate their journey into the digital future. Headquartered in Silicon Valley, the company operates design studios and engineering centers globally, serving diverse industries such as automotive, communications, financial services, healthcare, life sciences, manufacturing, media, entertainment, semiconductors, and technology. As a Hitachi Group Company, GlobalLogic is committed to fostering a sustainable society through innovation using data and technology.

Stepping into a Data Engineer role at GlobalLogic, you’ll contribute to transforming industries through data-driven solutions. The position demands proficiency in big data ecosystems like Apache Spark, a strong understanding of ETL processes, and experience with cloud platforms such as Azure. You’ll be involved in designing scalable data pipelines, optimizing performance, and collaborating with stakeholders to deliver effective data solutions.

If you aspire to join a cutting-edge firm at the forefront of digital transformation, this guide will navigate you through the interview landscape, share frequently asked questions, and offer tips to help you succeed. Let’s dive in!

Submitting Your Application

To kickstart your journey with GlobalLogic, the first step is to submit a well-tailored application that showcases your technical skills and eagerness to join their dynamic team. Whether you’ve been reached out by a GlobalLogic recruiter or have proactively applied, it’s crucial to carefully review the job description and align your CV to meet the requirements.

Customizing your resume might include pinpointing specific keywords that the hiring manager may use to filter through applications and writing a targeted cover letter. Make sure to prominently display your relevant skills and past work experiences.

Recruiter/Hiring Manager Call Screening

If your CV catches the eye of the hiring team, a recruiter from GlobalLogic will reach out to verify key details such as your background, project work, work authorization, and your readiness to relocate. This call might also include some 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 video conferencing and requires screen sharing. During this 1-hour session, expect to discuss your project experiences in detail and answer questions about specific technologies like Python, dataframe, 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 onsite 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 also soft skills like teamwork and problem-solving abilities.

Quick Tips For GlobalLogic Data Engineering Interviews

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

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

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.

• 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

• How does random forest generate the forest and why use it over logistic regression? Explain the process of how 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.

• 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.

• 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 success of the new model, such as accuracy, precision, recall, and AUC-ROC.

• 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.

• What are the key differences between classification models and regression models? Describe the main differences between classification and regression models, including their objectives, output types, and common use cases.

  Sure, here is the formatted list of questions with the corresponding links:

• How would you design a function to detect anomalies in univariate and bivariate datasets? If given a univariate dataset, how would you design a function to detect anomalies? What if the data is bivariate?

• 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.

• 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.

• 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.

• What are Z and t-tests, and when should you use each? Explain what Z and t-tests are, their uses, the differences between them, and when to use one over the other.

  Sure, I’ll format the questions and add the corresponding links as specified. Starting from question number 1:

1. What are the Z and t-tests, and when should you use each? Explain the purpose and differences between Z and t-tests. Describe scenarios where one test is preferred over the other.

2. What are the drawbacks of the given data layouts, and how would you reformat them for analysis? Analyze the provided student test score datasets. Identify drawbacks in their current format, suggest improvements, and discuss common issues in messy datasets.

3. 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 the value of each channel.

4. 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.

5. 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.

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

Q: What does GlobalLogic offer to Data Engineers? A: GlobalLogic offers exciting projects at the digital transformation forefront, 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.

Q: What skills are required for a Data Engineer position at GlobalLogic? A: 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.

Q: Can you describe the interview process at GlobalLogic for a Data Engineer role? A: The interview process typically starts with a screening call to discuss your background, project work, and relocation willingness. This is followed by a technical interview focusing on your familiarity with data engineering concepts, coding skills in languages like Python, and your ability to handle SQL queries, DataFrames, and tools like Apache Spark.

Q: What kinds of projects do Data Engineers work on at GlobalLogic? A: 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.

Q: How does GlobalLogic support career development for Data Engineers? A: 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.

As the digital landscape continues to evolve, GlobalLogic is at the forefront of digital engineering, consistently seeking talented Data Engineers to join its dynamic team.

By honing in on the core competencies and requirements outlined in the interview experiences and job postings, you can better position yourself to shine in the recruitment process. Demonstrate your deep understanding of ETL processes, big data ecosystems, and programming languages like Python and Scala, alongside your ability to explain complex technical projects clearly and effectively.

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

If you’re ready to take on new challenges and work on market-defining products, GlobalLogic could be your next big career move. Good luck with your interview!