PSEG Data Engineer Interview Questions + Guide in 2025

PSEG is a leading energy provider, committed to delivering safe, reliable, and sustainable energy solutions to its customers and communities.

The Data Engineer role at PSEG involves the full technology life cycle, where you will be responsible for designing, coding, configuring, testing, implementing, and supporting application software that meets business and technology requirements. You will collaborate closely with analysts and product managers to understand business goals and translate them into technical solutions, particularly in the realm of data processing and analytics. Key responsibilities include developing data ingestion pipelines, managing ETL processes, and ensuring that technology solutions integrate seamlessly with existing systems while adhering to security and quality assurance standards.

Successful candidates will have strong experience in AWS Data Cloud development, proficiency in SQL and Python, and a solid understanding of data structures and algorithms. A proactive approach to troubleshooting, excellent problem-solving skills, and the ability to work in a fast-paced environment are essential traits for this role. Familiarity with agile methodologies and a collaborative mindset will also enhance your fit within PSEG’s culture of inclusivity and innovation.

This guide will help you prepare effectively for your interview by providing insights into the skills and competencies valued by PSEG, as well as the types of questions you can expect during the process.

The interview process for a Data Engineer position at PSEG is structured to assess both technical and behavioral competencies, ensuring candidates align with the company's values and technical requirements. The process typically unfolds in several stages:

1. Initial Screening

The first step involves a preliminary screening, often conducted by a recruiter. This may take the form of a phone or video interview where the recruiter will discuss the role, the company culture, and your background. Expect to answer questions about your experience, skills, and motivations for applying to PSEG.

2. Pre-Recorded Interview

Candidates may be required to complete a pre-recorded interview. This step allows you to respond to a set of predetermined questions at your convenience. It’s essential to prepare thoroughly, as you will need to articulate your experiences and problem-solving approaches clearly. Questions may focus on your technical skills, such as your experience with SQL, Python, and AWS services, as well as behavioral scenarios.

3. Technical Interview

Following the pre-recorded interview, candidates typically participate in a technical interview. This may involve one or more technical team members and can include live coding exercises or problem-solving scenarios. You should be prepared to demonstrate your knowledge of data engineering concepts, including ETL processes, data ingestion pipelines, and database management. Familiarity with AWS services and coding in Python or SQL will be crucial.

4. Behavioral Interview

The behavioral interview often follows the technical assessment and may involve a panel of interviewers. This round focuses on your past experiences and how they relate to the role. Expect to answer questions using the STAR (Situation, Task, Action, Result) format, highlighting your problem-solving skills, teamwork, and adaptability. Be ready to discuss specific instances where you overcame challenges or contributed to team success.

5. Final Interview

In some cases, a final interview may be conducted with senior management or team leads. This round may delve deeper into your fit within the company culture and your long-term career aspirations. It’s an opportunity for you to ask questions about the team dynamics, project expectations, and PSEG’s commitment to diversity and inclusion.

As you prepare for your interview, consider the types of questions that may arise in each of these stages, particularly those that relate to your technical expertise and past experiences.

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

Understand the Company Culture

PSEG emphasizes a culture of safety, inclusivity, and reliability. Familiarize yourself with their core values and how they align with your own. Be prepared to discuss how you can contribute to a positive work environment and support the company's commitment to diversity and community engagement. Showing that you resonate with their mission can set you apart from other candidates.

Prepare for Behavioral Questions

Expect a significant focus on behavioral questions during your interview. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Reflect on your past experiences, particularly those that demonstrate your problem-solving skills, teamwork, and adaptability. For instance, be ready to discuss a time when you overcame a technical challenge or how you handled a project that didn’t go as planned.

Highlight Technical Proficiency

As a Data Engineer, you will need to showcase your technical skills, particularly in SQL, Python, and AWS services. Be prepared to discuss your experience with ETL processes, data ingestion pipelines, and any relevant projects you've worked on. Consider bringing examples of your work or discussing specific challenges you faced and how you resolved them. This will demonstrate your hands-on experience and problem-solving abilities.

Engage with the Interviewers

During the interview, engage with your interviewers by asking insightful questions about the team, projects, and company direction. This not only shows your interest in the role but also helps you gauge if the company is the right fit for you. Questions about the technologies they use, the team dynamics, or upcoming projects can lead to a more interactive and memorable conversation.

Be Ready for Technical Assessments

You may encounter technical assessments or questions that require you to demonstrate your knowledge in real-time. Brush up on your coding skills and be prepared to solve problems on the spot. Practice common data engineering scenarios, such as designing a data pipeline or optimizing a database query. This will help you feel more confident and capable during the technical portions of the interview.

Show Your Problem-Solving Skills

PSEG values analytical thinking and problem-solving abilities. Be prepared to discuss how you approach complex problems, including your thought process and the tools you use. Highlight any experience you have with troubleshooting and resolving technical issues, as this is crucial for the role.

Follow Up Thoughtfully

After the interview, send a thoughtful thank-you email to your interviewers. Mention specific points from your conversation that resonated with you and reiterate your enthusiasm for the role. This not only shows your professionalism but also keeps you top of mind as they make their decision.

By following these tips and preparing thoroughly, you can present yourself as a strong candidate for the Data Engineer position at PSEG. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at PSEG. The interview process will likely assess both technical skills and behavioral competencies, focusing on your ability to design, implement, and support technology solutions while collaborating with various stakeholders. Be prepared to discuss your experience with data engineering, problem-solving, and your approach to working in a team environment.

Technical Skills

1. Can you explain the ETL process and how you have implemented it in your previous projects?

Understanding the ETL process is crucial for a Data Engineer, as it involves extracting data from various sources, transforming it into a suitable format, and loading it into a target system.

How to Answer

Discuss your experience with ETL tools and methodologies, emphasizing specific projects where you successfully implemented ETL processes. Highlight any challenges you faced and how you overcame them.

Example

“In my previous role, I utilized AWS Glue for ETL processes, extracting data from multiple sources, transforming it using Python scripts, and loading it into Amazon Redshift. One challenge was ensuring data quality during transformation, which I addressed by implementing validation checks at each stage of the process.”

2. Describe your experience with AWS services, particularly in building data pipelines.

AWS services are integral to PSEG's data engineering efforts, so familiarity with these tools is essential.

How to Answer

Detail your experience with specific AWS services like S3, Lambda, and Glue, and how you have used them to build data pipelines. Mention any relevant projects and the outcomes.

Example

“I have built data ingestion pipelines using AWS S3 for storage and AWS Lambda for processing. For instance, I created a pipeline that ingested real-time data from IoT devices, processed it with Lambda functions, and stored it in S3 for further analysis. This setup improved our data availability and reduced latency.”

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

Data integrity and security are paramount in any data engineering role, especially in a utility company like PSEG.

How to Answer

Discuss the measures you take to ensure data integrity and security, such as encryption, access controls, and regular audits. Provide examples of how you have implemented these measures in past projects.

Example

“I prioritize data integrity by implementing checksums during data transfers and using AWS IAM roles to control access to sensitive data. In a recent project, I set up encryption for data at rest and in transit, ensuring compliance with industry standards and protecting customer information.”

4. Can you walk us through a challenging data-related problem you encountered and how you resolved it?

This question assesses your problem-solving skills and ability to handle challenges in data engineering.

How to Answer

Use the STAR method (Situation, Task, Action, Result) to structure your response. Focus on a specific problem, your role in addressing it, and the outcome.

Example

“In a previous project, we faced significant delays in data processing due to inefficient queries. I analyzed the query performance and identified bottlenecks. By optimizing the SQL queries and indexing the database, I reduced processing time by 40%, which significantly improved our reporting capabilities.”

Behavioral Questions

5. Describe a time when you had to collaborate with cross-functional teams. How did you ensure effective communication?

Collaboration is key in a data engineering role, as you will often work with analysts, product managers, and other stakeholders.

How to Answer

Highlight your communication strategies and how you adapt your approach based on the audience. Provide an example of a successful collaboration.

Example

“I worked on a project where I collaborated with data analysts and product managers to develop a new reporting tool. I scheduled regular check-ins to discuss progress and gather feedback, ensuring everyone was aligned. This open communication led to a successful launch that met all stakeholders' needs.”

6. Tell me about a time when you had to adapt to a significant change in project requirements.

Flexibility is important in a fast-paced environment, and this question assesses your adaptability.

How to Answer

Discuss a specific instance where project requirements changed and how you adjusted your approach to meet the new demands.

Example

“During a project, the scope changed when the business decided to integrate additional data sources. I quickly reassessed our timeline and resources, communicated the changes to the team, and adjusted our ETL processes accordingly. This proactive approach allowed us to meet the new requirements without significant delays.”

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

Time management and prioritization are essential skills for a Data Engineer, especially when handling multiple projects.

How to Answer

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

Example

“I use a combination of project management tools like Jira and prioritization frameworks like the Eisenhower Matrix to manage my tasks. By categorizing tasks based on urgency and importance, I ensure that I focus on high-impact activities first, which helps me meet deadlines across multiple projects.”

8. What motivates you to work in data engineering, and how do you stay updated with industry trends?

This question gauges your passion for the field and commitment to continuous learning.

How to Answer

Share your motivations for pursuing a career in data engineering and the resources you use to stay informed about industry developments.

Example

“I am motivated by the potential of data to drive decision-making and improve processes. I regularly attend webinars, participate in online courses, and follow industry leaders on platforms like LinkedIn to stay updated on the latest trends and technologies in data engineering.”