CBRE Data Engineer Interview Questions + Guide in 2025

CBRE is a global leader in commercial real estate services and investment, dedicated to providing innovative solutions to clients across various sectors.

As a Data Engineer at CBRE, you will play a crucial role in designing, building, and maintaining data pipelines that support the company’s strategic decisions and enhance its operational efficiency. Key responsibilities include developing robust data architectures, integrating data from diverse sources, and ensuring data quality and accessibility for analytics teams. A strong understanding of database systems, ETL processes, and data modeling is essential. Familiarity with programming languages such as Python or SQL, as well as experience with cloud platforms, will give you a competitive edge. The ideal candidate will possess analytical thinking, attention to detail, and an ability to collaborate across departments, aligning with CBRE's commitment to innovation and excellence in service delivery.

This guide will help you prepare effectively for your interview by providing insights into the role and the types of questions you may encounter, increasing your confidence and readiness to impress your interviewers.

The interview process for a Data Engineer position at CBRE is structured and involves multiple stages to ensure a comprehensive evaluation of candidates.

1. Initial Screening

The process typically begins with an initial screening call conducted by a recruiter. This call lasts around 15 to 30 minutes and focuses on discussing the role, your background, and your motivations for applying. The recruiter will also assess your fit for the company culture and may touch upon salary expectations.

2. Technical Interview

Following the initial screening, candidates usually participate in a technical interview. This may be conducted via video conferencing and involves discussions around your technical skills, particularly in data engineering concepts, tools, and methodologies. Expect to answer questions related to your experience with data pipelines, database management, and any relevant programming languages or frameworks.

3. Panel Interview

The next step often includes a panel interview with multiple team members. This session is designed to evaluate both your technical and behavioral competencies. You may be asked to present past projects or experiences, and the panel will likely pose situational questions to gauge your problem-solving abilities and teamwork skills. This round typically lasts around 45 minutes to an hour.

4. Final Interview

The final stage usually involves an interview with a senior manager or director. This conversation is often more informal and focuses on your long-term career goals, how you envision contributing to the team, and your understanding of the commercial real estate market. This round may also include a discussion about your fit within the broader organizational structure.

5. Additional Assessments

In some cases, candidates may be required to complete additional assessments, such as a take-home coding challenge or a case study relevant to data engineering tasks. These assessments are designed to evaluate your practical skills and ability to apply your knowledge in real-world scenarios.

As you prepare for your interview, be ready to discuss your experiences and how they relate to the role, as well as to answer behavioral questions that reflect your problem-solving and teamwork capabilities.

Next, let’s delve into the specific interview questions that candidates have encountered during the process.

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

Understand the Interview Structure

The interview process at CBRE typically involves multiple stages, including an initial screening call, followed by interviews with team members and possibly a senior director. Familiarize yourself with this structure so you can prepare accordingly. Knowing what to expect will help you feel more at ease and allow you to focus on showcasing your skills and experiences.

Prepare for Behavioral Questions

CBRE places a strong emphasis on behavioral interview questions. Be ready to discuss your past experiences in detail, particularly how you've handled challenges, collaborated with teams, and contributed to projects. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you highlight your problem-solving abilities and the lessons learned from each experience.

Showcase Your Technical Skills

As a Data Engineer, you will likely face technical questions related to data management, SQL, and possibly coding challenges. Brush up on your technical skills and be prepared to discuss your experience with data pipelines, ETL processes, and any relevant tools or technologies. If you have examples of past projects, be ready to explain your methodologies and the impact of your work.

Be Ready for Cultural Fit Questions

CBRE values a collaborative and friendly work environment. Expect questions that assess your fit within the company culture. Be prepared to discuss your long-term career goals and how they align with CBRE's mission and values. Demonstrating that you understand and appreciate the company culture will help you stand out as a candidate.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers. This not only shows your interest in the role but also gives you a chance to assess if CBRE is the right fit for you. Inquire about team dynamics, ongoing projects, and how success is measured within the role. This will also help you gauge the company's commitment to employee development and collaboration.

Follow Up Professionally

After your interviews, send a thank-you email to express your appreciation for the opportunity to interview. This is a chance to reiterate your interest in the position and briefly mention any key points from the interview that you found particularly engaging. A well-crafted follow-up can leave a lasting impression and demonstrate your professionalism.

By following these tips, you can approach your interview with confidence and clarity, positioning yourself as a strong candidate for the Data Engineer role at CBRE. Good luck!

Experience and Background

1. Can you describe your previous experience in data engineering and how it relates to this role?

This question aims to assess your relevant background and how it aligns with the expectations of the position.

How to Answer

Highlight specific projects or roles where you utilized data engineering skills, focusing on technologies and methodologies that are relevant to CBRE.

Example

“In my previous role at XYZ Corp, I was responsible for designing and implementing data pipelines using Apache Spark and AWS. I successfully reduced data processing time by 30% through optimization techniques, which directly improved our reporting capabilities.”

2. What are your long-term career goals, and how does this position fit into them?

This question helps the interviewer understand your aspirations and whether they align with the company's direction.

How to Answer

Discuss your career trajectory and how the role at CBRE will help you achieve your professional objectives.

Example

“I aim to become a lead data engineer within the next five years, focusing on developing scalable data solutions. This position at CBRE is a perfect fit as it offers opportunities to work on large-scale projects and collaborate with cross-functional teams.”

3. Why are you interested in working for CBRE?

This question assesses your motivation for applying and your knowledge of the company.

How to Answer

Express your enthusiasm for the company’s mission and values, and mention specific aspects of CBRE that attract you.

Example

“I admire CBRE’s commitment to innovation in the commercial real estate sector. The opportunity to work with cutting-edge data technologies to drive business decisions aligns perfectly with my passion for data engineering.”

4. How would your friends describe you?

This question is designed to gauge your self-awareness and interpersonal skills.

How to Answer

Choose traits that reflect positively on your work ethic and teamwork abilities.

Example

“My friends would describe me as analytical and supportive. They often mention my ability to break down complex problems and help others understand them, which I believe is crucial in a collaborative work environment.”

Technical Skills

1. What is your experience with SQL and how have you used it in your previous roles?

This question evaluates your technical proficiency with SQL, a critical skill for data engineers.

How to Answer

Provide specific examples of how you have used SQL to manipulate and analyze data.

Example

“I have extensive experience with SQL, having used it to create complex queries for data extraction and reporting. In my last project, I developed a series of SQL scripts that automated data retrieval, which saved the team several hours each week.”

2. Can you explain the difference between structured and unstructured data?

This question tests your understanding of data types and their implications for data engineering.

How to Answer

Define both terms and provide examples of each, emphasizing their relevance in data processing.

Example

“Structured data is organized and easily searchable, typically found in relational databases, while unstructured data lacks a predefined format, such as emails or social media posts. Understanding these differences is crucial for designing effective data storage solutions.”

3. Describe a challenging data engineering project you worked on and how you overcame the obstacles.

This question assesses your problem-solving skills and resilience.

How to Answer

Detail the project, the challenges faced, and the strategies you employed to overcome them.

Example

“In a previous project, we faced significant data quality issues that delayed our timeline. I initiated a data cleansing process, collaborating with the team to identify and rectify inconsistencies, which ultimately led to successful project completion.”

4. What tools and technologies are you proficient in for data engineering?

This question evaluates your technical toolkit and readiness for the role.

How to Answer

List the tools you are familiar with, focusing on those relevant to the job description.

Example

“I am proficient in tools such as Apache Spark, AWS, and Tableau. I have also worked with Python for data manipulation and ETL processes, which I believe are essential for this role.”

Behavioral Questions

1. Give an example of a time you failed and what you learned from it.

This question explores your ability to learn from mistakes and grow professionally.

How to Answer

Choose a specific instance, explain the failure, and focus on the lessons learned.

Example

“During a project, I underestimated the time required for data migration, which led to delays. I learned the importance of thorough planning and stakeholder communication, which I now prioritize in all my projects.”

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

This question assesses your organizational skills and ability to manage time effectively.

How to Answer

Discuss your approach to prioritization and any tools or methods you use.

Example

“I prioritize tasks based on deadlines and project impact. I use project management tools like Trello to keep track of my responsibilities and ensure that I allocate time effectively across all projects.”

3. Describe a time when you had to collaborate with a difficult stakeholder.

This question evaluates your interpersonal skills and ability to navigate challenging situations.

How to Answer

Provide a specific example, focusing on your approach to communication and resolution.

Example

“I once worked with a stakeholder who was resistant to change. I scheduled a meeting to understand their concerns and provided data-driven insights to demonstrate the benefits of the proposed changes, which ultimately led to a successful collaboration.”

4. What do you think the job role entails?

This question assesses your understanding of the position and its responsibilities.

How to Answer

Summarize your understanding of the role based on the job description and your research.

Example

“I believe the role entails designing and maintaining data pipelines, ensuring data quality, and collaborating with cross-functional teams to support data-driven decision-making within the organization.”