ViacomCBS Data Engineer Interview Questions + Guide in 2025

ViacomCBS is a global media and entertainment company, known for delivering compelling content across various platforms and reaching a diverse audience worldwide.

As a Data Engineer at ViacomCBS, you will play a critical role in building and maintaining the architecture that supports data processing and analytics. Key responsibilities include designing and implementing data pipelines, ensuring data integrity and quality, and collaborating with data scientists and analysts to facilitate data-driven decision-making. An ideal candidate will possess strong technical skills in SQL, Python, and data modeling, along with a solid understanding of data warehousing and ETL processes. Experience in cloud technologies and familiarity with big data tools will set you apart, as these are essential for managing the scale and complexity of the data ViacomCBS handles.

Emphasizing the company's commitment to innovation and storytelling, your role as a Data Engineer will directly contribute to enhancing the quality and accessibility of data that fuels the company's creative and strategic initiatives. This guide will help you prepare for your interview by providing insights into the specific skills and experiences ViacomCBS values in a Data Engineer.

The interview process for a Data Engineer position at ViacomCBS is structured to assess both technical skills and cultural fit within the organization. The process typically unfolds in several key stages:

1. Initial Phone Interview

The first step is an initial phone interview, usually conducted by a recruiter or HR representative. This conversation lasts about 30 minutes and focuses on your background, experiences, and motivations for applying to ViacomCBS. The recruiter will also gauge your understanding of the role and the company culture, as well as your interest in the media and entertainment industry.

2. Technical Interview

Following the initial screening, candidates can expect a technical interview. This stage may be conducted via video call and typically involves a data engineering professional from the team. During this interview, you will be assessed on your technical competencies, including your knowledge of data pipelines, ETL processes, and database management. Be prepared to discuss your previous projects and how you have applied your technical skills in real-world scenarios.

3. Onsite Interview

The final stage of the interview process is the onsite interview, which may consist of multiple rounds with various team members. Each round will focus on different aspects of the data engineering role, including system design, data architecture, and problem-solving skills. You may also encounter behavioral questions aimed at understanding how you collaborate with others and handle challenges in a team environment. This stage is crucial for demonstrating your technical expertise and your ability to fit within the team dynamics.

As you prepare for your interviews, it's essential to familiarize yourself with the specific skills and competencies that are highly valued in this role. Next, we will delve into the types of questions you might encounter during the interview process.

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

Understand the Company’s Vision and Values

Before your interview, take the time to familiarize yourself with ViacomCBS's mission, values, and recent initiatives. Understanding how the company positions itself in the media landscape and its approach to technology will help you align your responses with their goals. Be prepared to discuss how your skills as a Data Engineer can contribute to their projects and overall vision.

Prepare for Technical Assessments

As a Data Engineer, you will likely face technical assessments that evaluate your proficiency in data modeling, ETL processes, and database management. Brush up on your knowledge of data warehousing concepts, data pipeline architecture, and relevant programming languages. Be ready to demonstrate your problem-solving skills through practical exercises or coding challenges that may be part of the interview process.

Anticipate Behavioral Questions

Expect behavioral questions that assess your teamwork, communication, and adaptability. ViacomCBS values collaboration, so be prepared to share examples of how you have worked effectively in teams, resolved conflicts, or adapted to changing project requirements. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you highlight your contributions and the impact of your work.

Show Enthusiasm for the Role

During the interview, express genuine enthusiasm for the Data Engineer position and the opportunity to work at ViacomCBS. Share specific reasons why you are excited about the role, such as the chance to work with cutting-edge technologies or contribute to innovative projects in the media industry. This enthusiasm can set you apart from other candidates and demonstrate your commitment to the company.

Follow Up Professionally

After your interview, send a thoughtful follow-up email to thank your interviewers for their time and reiterate your interest in the position. This is not only a courteous gesture but also an opportunity to reinforce your qualifications and enthusiasm for the role. Mention any specific topics discussed during the interview that resonated with you, which can help keep you top of mind as they make their decision.

By following these tips, you can present yourself as a well-prepared and enthusiastic candidate, ready to contribute to the innovative work at ViacomCBS as a Data Engineer. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at ViacomCBS. The interview process will likely focus on your technical skills, problem-solving abilities, and understanding of data architecture and engineering principles. Be prepared to discuss your experience with data pipelines, ETL processes, and database management.

Technical Skills

1. Can you explain the ETL process and its importance in data engineering?

Understanding the ETL (Extract, Transform, Load) process is crucial for a Data Engineer, as it is a fundamental part of data management and integration.

How to Answer

Discuss the steps involved in ETL and emphasize its role in ensuring data quality and accessibility for analysis.

Example

“The ETL process involves extracting data from various sources, transforming it into a suitable format, and loading it into a data warehouse. This process is vital as it ensures that data is clean, consistent, and readily available for analytics, which ultimately drives informed decision-making.”

2. What are some common data storage solutions you have worked with?

This question assesses your familiarity with different data storage technologies and your ability to choose the right one for specific use cases.

How to Answer

Mention specific databases or storage solutions you have experience with, and explain the scenarios in which you would use each.

Example

“I have worked with both SQL databases like PostgreSQL for structured data and NoSQL solutions like MongoDB for unstructured data. For instance, I prefer using PostgreSQL when data integrity and complex queries are essential, while MongoDB is ideal for applications requiring high scalability and flexibility.”

Data Modeling

3. How do you approach designing a data model for a new application?

This question evaluates your understanding of data modeling principles and your ability to create efficient data structures.

How to Answer

Outline your process for gathering requirements, identifying entities, and defining relationships, while considering performance and scalability.

Example

“When designing a data model, I start by gathering requirements from stakeholders to understand the data needs. I then identify key entities and their relationships, ensuring normalization to reduce redundancy. Finally, I consider indexing strategies to optimize query performance.”

4. Can you describe a challenging data engineering 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

Choose a project that highlights your technical skills and the impact of your work, focusing on the challenges faced and how you overcame them.

Example

“In a recent project, I was tasked with migrating a legacy data system to a cloud-based solution. The challenge was ensuring data integrity during the transition. I developed a comprehensive migration plan that included data validation checks and a rollback strategy, which ultimately led to a successful migration with minimal downtime.”

Programming and Tools

5. What programming languages and tools do you prefer for data engineering tasks?

This question assesses your technical proficiency and familiarity with industry-standard tools.

How to Answer

Mention the programming languages and tools you are comfortable with, and explain why you prefer them for specific tasks.

Example

“I primarily use Python for data manipulation and ETL tasks due to its extensive libraries like Pandas and NumPy. For orchestration, I prefer Apache Airflow, as it allows for easy scheduling and monitoring of workflows, which is essential for maintaining data pipelines.”

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

This question evaluates your understanding of data quality principles and the measures you take to maintain it.

How to Answer

Discuss the techniques and tools you use to monitor and validate data quality throughout the data lifecycle.

Example

“To ensure data quality, I implement validation checks at various stages of the ETL process, such as schema validation and data profiling. Additionally, I use tools like Great Expectations to automate data quality testing, which helps catch issues early and maintain data integrity.”

Collaboration and Communication

7. How do you collaborate with data scientists and analysts in your role?

This question assesses your ability to work in a team and communicate effectively with other stakeholders.

How to Answer

Highlight your experience in cross-functional collaboration and how you ensure that data needs are met.

Example

“I regularly collaborate with data scientists and analysts by participating in requirement-gathering sessions and providing them with the necessary data infrastructure. I also ensure clear communication regarding data availability and any limitations, which helps align our goals and facilitates smoother project execution.”

8. Describe a time when you had to explain a technical concept to a non-technical audience.

This question evaluates your communication skills and ability to convey complex information clearly.

How to Answer

Choose an example that demonstrates your ability to simplify technical jargon and engage your audience.

Example

“During a project update, I had to explain our data pipeline architecture to the marketing team. I used visual aids to illustrate the flow of data and avoided technical jargon, focusing instead on how the data would support their campaigns. This approach helped them understand the value of our work and fostered better collaboration.”