Educational Testing Service (ETS) Data Engineer Interview Questions + Guide in 2025

Educational Testing Service (ETS) is a globally recognized organization dedicated to advancing quality and equity in education through trusted assessments and innovative solutions.

The Data Engineer role at ETS is pivotal in managing and optimizing data architecture, ensuring that data is effectively collected, processed, and utilized to drive insights and empower educational solutions. Key responsibilities include designing and implementing scalable data frameworks, developing cloud data platforms, and maintaining data quality standards. A successful candidate will have extensive experience in database development, data modeling, and cloud technologies, coupled with strong SQL skills. Importantly, the role requires excellent communication skills to convey complex technical concepts to non-technical stakeholders, fostering collaboration across teams. The ideal Data Engineer will align their work with ETS's mission to enable lifelong learning and promote skill development, reflecting the company's commitment to continuous improvement and innovation in educational assessment.

This guide will provide you with tailored insights to prepare for your interview, helping you navigate questions and demonstrate your fit for the Data Engineer role at ETS.

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

1. Initial Screening

The process begins with an initial screening, usually conducted by a recruiter. This 30-minute phone interview focuses on understanding your background, motivations for applying, and basic qualifications. The recruiter will also provide insights into the company culture and the specific role, ensuring that candidates have a clear understanding of what to expect.

2. Technical Assessment

Following the initial screening, candidates may be required to complete a technical assessment. This could involve a coding challenge or a take-home project that tests your proficiency in SQL, Python, and data modeling. The assessment is designed to evaluate your problem-solving skills and your ability to work with data architecture concepts relevant to the role.

3. Technical Interviews

Candidates who pass the technical assessment will move on to one or more technical interviews. These interviews typically involve discussions with data engineers or technical leads and may include questions about data architecture, ETL processes, and cloud platforms such as Azure or AWS. Expect to demonstrate your understanding of data integration techniques, database management, and your experience with big data technologies.

4. Behavioral Interviews

In addition to technical skills, ETS places a strong emphasis on cultural fit and collaboration. Behavioral interviews will focus on your past experiences, teamwork, and how you handle challenges. You may be asked to provide specific examples of how you've contributed to projects, managed conflicts, or adapted to changing priorities in a work environment.

5. Panel Interview

The final stage often includes a panel interview with multiple stakeholders, including potential colleagues and managers. This session may involve a presentation where you articulate your approach to a data-related problem or project. The panel will assess not only your technical knowledge but also your communication skills and ability to engage with a diverse group of professionals.

Throughout the interview process, candidates should be prepared to discuss their previous work experiences, particularly those that relate to data architecture and engineering.

Next, let's delve into the specific interview questions that candidates have encountered during their interviews at ETS.

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

Understand the Company Culture

Educational Testing Service (ETS) values diversity, equity, and inclusion, which are integral to their mission. Familiarize yourself with their commitment to these principles and be prepared to discuss how your own values align with theirs. Highlight any experiences that demonstrate your commitment to fostering an inclusive environment, as this will resonate well with the interviewers.

Prepare for a Multi-Round Interview Process

The interview process at ETS can be extensive, often involving multiple rounds with various stakeholders, including peers and executives. Be ready to articulate your experiences and how they relate to the role of a Data Engineer. Prepare to discuss your technical skills in SQL, data architecture, and cloud platforms, as well as your ability to collaborate with cross-functional teams. Practicing your responses to common behavioral questions will also be beneficial.

Showcase Your Technical Expertise

Given the emphasis on SQL and data architecture in the role, ensure you are well-versed in these areas. Be prepared to discuss specific projects where you utilized SQL for data manipulation and analysis. Familiarize yourself with cloud data platforms like Azure and AWS, as well as data modeling and ETL processes. You may be asked to solve technical problems or provide examples of how you’ve approached data challenges in the past.

Communicate Clearly and Effectively

ETS values the ability to convey complex technical concepts to non-technical stakeholders. Practice explaining your past projects in a way that is accessible to someone without a technical background. This skill will be crucial during your interviews, especially when discussing your architectural vision and how it aligns with the organization’s goals.

Be Ready for Generic Questions

While the interviewers may ask some generic questions, such as "Tell me about yourself," use these opportunities to highlight your relevant experiences and how they connect to the role. Tailor your responses to reflect your understanding of ETS's mission and how you can contribute to their goals.

Follow Up Professionally

After your interviews, consider sending a thank-you email to express your appreciation for the opportunity to interview. This not only demonstrates professionalism but also reinforces your interest in the position. If you experience delays in communication, remain patient but proactive in following up to inquire about your application status.

Stay Adaptable

The interview process may not always follow a clear path, and you might encounter unexpected questions or scenarios. Stay adaptable and maintain a positive attitude throughout the process. Show that you can handle ambiguity and are willing to learn and grow within the organization.

By preparing thoroughly and aligning your experiences with ETS'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 Educational Testing Service (ETS). The interview process will likely focus on your technical skills, experience with data architecture, and your ability to communicate complex concepts effectively. Be prepared to discuss your past projects, your understanding of data management principles, and how you can contribute to the organization's goals.

Technical Skills

1. Can you explain the differences between SQL and NoSQL databases?

Understanding the distinctions between these database types is crucial for a Data Engineer role, especially in a data-driven organization like ETS.

How to Answer

Discuss the fundamental differences in structure, scalability, and use cases for SQL and NoSQL databases. Highlight scenarios where one might be preferred over the other.

Example

"SQL databases are structured and use a predefined schema, making them ideal for complex queries and transactions. In contrast, NoSQL databases are more flexible, allowing for unstructured data storage, which is beneficial for applications requiring scalability and rapid data retrieval, such as real-time analytics."

2. Describe your experience with ETL processes.

This question assesses your practical knowledge of data extraction, transformation, and loading, which is essential for data integration tasks.

How to Answer

Provide specific examples of ETL tools you have used and the processes you implemented. Discuss any challenges you faced and how you overcame them.

Example

"I have extensive experience with ETL processes using tools like Apache NiFi and Talend. In my previous role, I designed an ETL pipeline that integrated data from multiple sources, ensuring data quality and consistency. One challenge was handling data discrepancies, which I resolved by implementing validation checks during the transformation phase."

3. What is your approach to data modeling?

Data modeling is a critical skill for a Data Engineer, and your answer should reflect your understanding of conceptual, logical, and physical models.

How to Answer

Explain your methodology for creating data models and how you ensure they meet business requirements. Mention any tools you use for data modeling.

Example

"I approach data modeling by first gathering business requirements to understand the data needs. I then create conceptual models to outline the data entities and their relationships, followed by logical models that define the structure without getting into implementation details. Finally, I develop physical models tailored to the specific database technology, using tools like ERwin for visualization."

4. How do you ensure data quality in your projects?

Data quality is paramount in any data-driven organization, and your answer should demonstrate your commitment to maintaining high standards.

How to Answer

Discuss the strategies and tools you use to monitor and improve data quality throughout the data lifecycle.

Example

"I ensure data quality by implementing validation rules during data entry and transformation processes. I also conduct regular audits and use tools like Apache Airflow to automate data quality checks. Additionally, I encourage a culture of data stewardship within the team to promote accountability."

5. Can you describe a challenging data integration project you worked on?

This question allows you to showcase your problem-solving skills and technical expertise in a real-world context.

How to Answer

Detail the project, the challenges you faced, and the solutions you implemented. Highlight the impact of your work on the organization.

Example

"I worked on a project that required integrating data from disparate systems, including legacy databases and cloud services. The main challenge was ensuring data consistency across platforms. I implemented a data governance framework and used Apache Kafka for real-time data streaming, which significantly improved data accuracy and reduced latency."

Communication and Collaboration

1. How do you communicate complex technical concepts to non-technical stakeholders?

Effective communication is key in a collaborative environment, especially when working with cross-functional teams.

How to Answer

Share your strategies for simplifying technical jargon and ensuring understanding among non-technical team members.

Example

"I focus on using analogies and visual aids to explain complex concepts. For instance, when discussing data pipelines, I compare them to water pipes, illustrating how data flows from one point to another. I also encourage questions to ensure everyone is on the same page."

2. Describe a time when you had to collaborate with a team to achieve a goal.

This question assesses your teamwork skills and ability to work effectively with others.

How to Answer

Provide a specific example of a collaborative project, your role in the team, and the outcome.

Example

"In a recent project, I collaborated with data scientists and product managers to develop a new analytics dashboard. My role was to ensure the data infrastructure supported their needs. We held regular meetings to align our goals, and the project resulted in a 30% increase in user engagement due to improved data accessibility."

3. How do you handle feedback and criticism from peers?

Your ability to accept and act on feedback is crucial for personal and professional growth.

How to Answer

Discuss your approach to receiving feedback and how you use it to improve your work.

Example

"I view feedback as an opportunity for growth. When I receive constructive criticism, I take time to reflect on it and identify actionable steps for improvement. For example, after receiving feedback on my documentation style, I adopted a more structured format, which has since been well-received by my team."

4. Why do you want to work at ETS?

This question gauges your motivation and alignment with the company's mission and values.

How to Answer

Express your interest in ETS's mission and how your skills and values align with the organization.

Example

"I am passionate about education and believe in ETS's mission to advance quality and equity in education. I am excited about the opportunity to leverage my data engineering skills to contribute to meaningful assessments that empower learners worldwide."

5. What are your top priorities if hired for this position?

This question allows you to demonstrate your understanding of the role and your proactive approach.

How to Answer

Outline your immediate goals and how they align with the organization's objectives.

Example

"If hired, my top priorities would be to assess the current data architecture, identify areas for improvement, and establish best practices for data governance. I would also focus on building strong relationships with cross-functional teams to ensure our data solutions effectively support their needs."