PPG Industries Data Engineer Interview Questions + Guide in 2025

PPG Industries is a global leader in coatings and specialty materials, dedicated to innovation and sustainability in the manufacturing sector.

As a Data Engineer at PPG Industries, you will play a crucial role in transforming raw data into actionable insights that drive business decisions and enhance operational efficiency. Key responsibilities include designing, building, and maintaining scalable data pipelines, ensuring data integrity, and collaborating with cross-functional teams to support data-driven projects. You will utilize SQL and Python to extract, manipulate, and analyze data from various sources, while also implementing algorithms to optimize data processing and storage. A strong understanding of analytics and product metrics will be essential to measure performance and inform strategic initiatives.

To excel in this role, you should possess excellent problem-solving skills, a keen attention to detail, and the ability to communicate complex technical concepts to non-technical stakeholders. Experience with cloud technologies and data warehousing solutions will also be beneficial. This position aligns with PPG's commitment to innovation, quality, and sustainability, as you will contribute to improving data systems that support the company's mission.

This guide will help you prepare for a job interview by providing insights into the expectations and skills relevant to the Data Engineer role at PPG Industries, setting you up for a successful interview experience.

The interview process for a Data Engineer at PPG Industries is structured to assess both technical skills and cultural fit within the organization. It typically consists of multiple rounds, each designed to evaluate different aspects of a candidate's qualifications and experiences.

1. Initial Phone Screening

The process begins with an initial phone screening, usually conducted by a recruiter or HR representative. This call lasts about 30 minutes and focuses on your background, relevant coursework, and work experience. Expect standard questions that gauge your interest in the role and the company, as well as your understanding of the position's requirements. This is also an opportunity for the recruiter to provide insights about the company culture and the specifics of the job.

2. Technical Interview

Following the initial screening, candidates typically undergo a technical interview, which may be conducted via video conferencing tools like Teams. This interview lasts about an hour and delves into your technical expertise, particularly in areas such as SQL and algorithms. You may be asked to solve problems or discuss past projects that demonstrate your analytical skills and familiarity with data engineering concepts. Be prepared to discuss your approach to data management, data pipelines, and any relevant programming languages you have experience with, such as Python.

3. Behavioral Interview

After the technical assessment, candidates often participate in a behavioral interview. This round may involve situational questions that assess how you handle challenges and collaborate with others. Expect questions that explore your leadership experiences, conflict resolution strategies, and how you adapt to changing circumstances. The interviewers will be looking for specific examples from your past experiences that illustrate your problem-solving abilities and teamwork skills.

4. Onsite Interview or Final Round

The final stage of the interview process may include an onsite interview or a comprehensive final round conducted virtually. This stage typically involves multiple interviewers, including team members and managers. You may be asked to present a project or case study relevant to the role, followed by a series of technical and behavioral questions. This round is designed to assess your fit within the team and your ability to communicate complex ideas effectively.

Throughout the interview process, candidates should be prepared to discuss their past projects in detail, as well as their motivations for wanting to work at PPG Industries.

Now that you have an understanding of the interview process, let's explore the types of questions you might encounter during your interviews.

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

Understand the Interview Structure

PPG Industries typically conducts multiple rounds of interviews, often starting with a phone screening followed by in-person interviews. Be prepared for at least two rounds, and expect a mix of behavioral and situational questions. Familiarize yourself with the common structure to help you feel more at ease during the process.

Prepare for Behavioral Questions

Behavioral questions are a significant part of the interview process at PPG. Expect to discuss past experiences, particularly those that demonstrate your problem-solving skills and ability to work in a team. Use the STAR method (Situation, Task, Action, Result) to structure your responses, ensuring you provide clear and concise examples that highlight your competencies.

Showcase Your Technical Expertise

As a Data Engineer, you will likely face questions that assess your technical skills. Be ready to discuss your experience with SQL, algorithms, and Python. Prepare to explain your past projects in detail, focusing on the tools and methodologies you used. This will not only demonstrate your technical proficiency but also your ability to communicate complex concepts effectively.

Emphasize Collaboration and Communication

PPG values teamwork and collaboration. Be prepared to discuss how you have worked with cross-functional teams in the past. Highlight your communication skills and your ability to navigate challenges in team settings. This will show that you can contribute positively to the company culture and work effectively with others.

Research the Company Culture

Understanding PPG's company culture is crucial. They value professionalism and direct communication, so approach the interview with a respectful and straightforward demeanor. Familiarize yourself with their core values and recent initiatives, as this knowledge can help you align your responses with what they prioritize in their employees.

Follow Up Professionally

After your interview, consider sending a follow-up email to express your gratitude for the opportunity and reiterate your interest in the position. This not only demonstrates professionalism but also keeps you on their radar, especially if there are delays in communication regarding your application status.

By preparing thoroughly and aligning your responses with PPG's values and expectations, you can position yourself as a strong candidate for the Data Engineer role. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at PPG Industries. The interview process will likely focus on your technical skills, problem-solving abilities, and how you handle various work situations. Be prepared to discuss your experience with data management, SQL, and algorithms, as well as your ability to work collaboratively in a team environment.

Technical Skills

1. Can you explain the difference between a clustered and a non-clustered index in SQL?

Understanding indexing is crucial for optimizing database performance, and this question tests your knowledge of SQL fundamentals.

How to Answer

Discuss the definitions of both types of indexes and their use cases, emphasizing how they affect data retrieval speed and storage.

Example

“A clustered index sorts and stores the data rows in the table based on the index key, which means there can only be one clustered index per table. In contrast, a non-clustered index creates a separate structure that points to the original table data, allowing for multiple non-clustered indexes on a table, which can improve query performance for specific search conditions.”

2. Describe a complex SQL query you have written and the problem it solved.

This question assesses your practical experience with SQL and your ability to solve real-world data problems.

How to Answer

Provide a brief overview of the problem, the SQL query you wrote, and the outcome. Highlight any challenges you faced and how you overcame them.

Example

“I once had to analyze customer purchase patterns across multiple regions. I wrote a complex SQL query that involved multiple joins and subqueries to aggregate data from different tables. This allowed us to identify trends and tailor our marketing strategies, resulting in a 15% increase in sales in the targeted regions.”

3. How do you ensure data quality and integrity in your projects?

Data quality is critical in data engineering, and this question evaluates your approach to maintaining high standards.

How to Answer

Discuss the methods you use to validate data, such as automated testing, data profiling, and regular audits.

Example

“I implement data validation checks at various stages of the data pipeline, including schema validation and anomaly detection. Additionally, I conduct regular audits and use automated testing frameworks to ensure that the data remains accurate and consistent throughout its lifecycle.”

4. What is your experience with ETL processes?

This question gauges your familiarity with Extract, Transform, Load (ETL) processes, which are essential in data engineering.

How to Answer

Share your experience with specific ETL tools and frameworks, and describe a project where you successfully implemented an ETL process.

Example

“I have extensive experience with ETL processes using tools like Apache NiFi and Talend. In a recent project, I designed an ETL pipeline that extracted data from various sources, transformed it to meet business requirements, and loaded it into a data warehouse. This streamlined our reporting process and improved data accessibility for stakeholders.”

Behavioral Questions

5. Tell us about a time you made a mistake in your work and how you handled it.

This question assesses your accountability and problem-solving skills.

How to Answer

Be honest about a mistake, explain what you learned from it, and describe the steps you took to rectify the situation.

Example

“During a project, I misconfigured a data pipeline, which led to incorrect data being loaded into our reporting system. I immediately notified my team, corrected the configuration, and implemented additional checks to prevent similar issues in the future. This experience taught me the importance of thorough testing before deployment.”

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

This question evaluates your time management and organizational skills.

How to Answer

Discuss your approach to prioritization, including any tools or methods you use to manage your workload effectively.

Example

“I prioritize tasks based on project deadlines and the impact of each task on overall project goals. I use project management tools like Trello to keep track of my tasks and regularly communicate with my team to ensure alignment on priorities.”

7. Describe a situation where you had to collaborate with a difficult team member.

This question assesses your interpersonal skills and ability to work in a team.

How to Answer

Share a specific example, focusing on how you approached the situation and what the outcome was.

Example

“I once worked with a team member who was resistant to feedback. I scheduled a one-on-one meeting to discuss our project goals and listened to their concerns. By fostering open communication, we were able to find common ground and improve our collaboration, ultimately leading to a successful project completion.”

8. Where do you see yourself in five years?

This question helps interviewers understand your career aspirations and commitment to the role.

How to Answer

Discuss your professional goals and how they align with the company’s objectives, showing your interest in growth within the organization.

Example

“In five years, I see myself taking on more leadership responsibilities within the data engineering team, possibly leading projects that drive innovation in data management. I am excited about the potential for growth at PPG and contributing to its mission through advanced data solutions.”