CACI International Inc Data Engineer Interview Questions + Guide in 2025

CACI International Inc is a prominent provider of technology solutions and services aimed at supporting national security and defense.

The Data Engineer role at CACI involves the design, implementation, and maintenance of robust data pipelines and architecture to facilitate the seamless flow and integrity of data across various systems. Key responsibilities include developing and optimizing ETL processes, ensuring data quality, and collaborating with data scientists and analysts to understand data needs. Ideal candidates should possess strong knowledge in data architecture, experience with big data technologies, and proficiency in programming languages such as SQL and Python. Furthermore, familiarity with cloud platforms like Azure and AWS, as well as knowledge of Agile methodologies, will align seamlessly with CACI's focus on innovation and integrity in its mission to support national security.

This guide will equip you with the necessary insights and preparation to tackle the interview confidently, helping you showcase your skills and fit for the role effectively.

The interview process for a Data Engineer position at CACI is structured to assess both technical skills and cultural fit within the organization. Candidates can expect a multi-step process that includes various types of interviews and assessments.

1. Initial Phone Screen

The process typically begins with an initial phone screen conducted by a recruiter. This conversation lasts about 30 to 60 minutes and focuses on understanding the candidate's background, experience, and motivations for applying. The recruiter will also provide an overview of the role and the company culture, ensuring that candidates have a clear understanding of what to expect.

2. Technical Assessment

Following the initial screen, candidates may be required to complete a technical assessment. This could involve a coding assignment or a take-home test that evaluates the candidate's proficiency in relevant programming languages and data engineering concepts. The assessment is designed to gauge the candidate's ability to handle real-world data challenges and their familiarity with tools and technologies commonly used in data engineering.

3. Technical Interview

Candidates who successfully complete the technical assessment will move on to a technical interview, which is typically conducted via video call. This interview may involve one or more technical team members and will focus on specific technical skills, including data architecture, ETL processes, and big data technologies. Candidates should be prepared to discuss their previous projects, problem-solving approaches, and demonstrate their understanding of data engineering principles.

4. Behavioral Interview

In addition to technical skills, CACI places a strong emphasis on cultural fit. Candidates will likely participate in a behavioral interview, where they will be asked to provide examples of past experiences that demonstrate their teamwork, communication skills, and ability to handle challenges. This interview may involve multiple interviewers, including managers and team leads, who will assess how well the candidate aligns with CACI's values and work environment.

5. Final Interview

The final step in the interview process may involve a more in-depth discussion with senior management or project leads. This interview is an opportunity for candidates to ask questions about the team, projects, and company direction. It also allows the interviewers to evaluate the candidate's long-term potential within the organization.

Throughout the process, candidates should be prepared to discuss their technical expertise, past experiences, and how they can contribute to CACI's mission.

Next, let's explore the specific interview questions that candidates have encountered during the process.

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

Understand the Company Culture

CACI values integrity, trust, and continuous growth. Familiarize yourself with these core principles and think about how your personal values align with them. During the interview, express your commitment to these values and provide examples from your past experiences that demonstrate your alignment with CACI's mission to ensure national security.

Be Prepared for a Mix of Technical and Behavioral Questions

Interviews at CACI often include both technical and behavioral questions. Prepare to discuss your technical skills in data engineering, such as ETL processes, data architecture, and relevant programming languages like SQL and Python. Additionally, be ready to share experiences that showcase your problem-solving abilities, teamwork, and adaptability. Use the STAR (Situation, Task, Action, Result) method to structure your responses effectively.

Highlight Your Clearance and Relevant Experience

Since many positions at CACI require security clearances, be sure to mention your current clearance status early in the conversation. Discuss your relevant experience in data engineering, particularly in environments similar to CACI's focus on defense and intelligence. This will help establish your credibility and suitability for the role.

Emphasize Collaboration and Communication Skills

CACI places a strong emphasis on teamwork and communication. Be prepared to discuss how you have successfully collaborated with cross-functional teams in the past. Share specific examples of how you communicated complex technical concepts to non-technical stakeholders, as this will demonstrate your ability to bridge gaps between technical and non-technical team members.

Show Enthusiasm for Continuous Learning

CACI values employees who are dedicated to continuous improvement and learning. Discuss any recent training, certifications, or self-directed learning you have undertaken to stay current in the field of data engineering. This will show your commitment to professional growth and your proactive approach to keeping your skills sharp.

Prepare for a Panel Interview Format

Many candidates report experiencing panel interviews at CACI, where multiple interviewers ask questions simultaneously. Practice answering questions in a way that engages all panel members. Make eye contact with each interviewer and address your responses to the group rather than just one person. This will help create a more inclusive atmosphere and demonstrate your ability to handle group dynamics.

Be Ready for Practical Assessments

Some interview processes may include practical assessments or coding challenges. Brush up on your coding skills and be prepared to demonstrate your problem-solving process in real-time. Familiarize yourself with common data engineering tasks and be ready to discuss your thought process as you work through these challenges.

Ask Insightful Questions

At the end of the interview, take the opportunity to ask thoughtful questions about the team, projects, and company culture. This not only shows your interest in the role but also helps you gauge if CACI is the right fit for you. Consider asking about the team’s current challenges, how success is measured, or opportunities for professional development within the company.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Engineer role at CACI International Inc. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at CACI International Inc. The interview process will likely assess your technical skills, problem-solving abilities, and how well you fit within the company culture. Be prepared to discuss your experience with data architecture, ETL processes, and your ability to work collaboratively in a team environment.

Technical Skills

1. Can you describe your experience with ETL processes and the tools you have used?

This question aims to gauge your familiarity with data extraction, transformation, and loading processes, which are crucial for a Data Engineer role.

How to Answer

Discuss specific ETL tools you have used, such as Azure Data Factory or Apache NiFi, and provide examples of how you implemented ETL processes in past projects.

Example

“I have extensive experience with Azure Data Factory, where I designed and implemented ETL pipelines to extract data from various sources, transform it into a usable format, and load it into our data warehouse. For instance, I automated the data ingestion process for a client’s sales data, which improved data availability by 30%.”

2. What is your approach to ensuring data quality and integrity?

This question assesses your understanding of data governance and quality assurance practices.

How to Answer

Explain the methods you use to validate and cleanse data, as well as any tools or frameworks you have implemented to maintain data integrity.

Example

“I prioritize data quality by implementing validation checks at each stage of the ETL process. I use tools like Apache Airflow to monitor data pipelines and ensure that any anomalies are flagged for review. Additionally, I conduct regular audits to verify data accuracy and consistency.”

3. Describe a challenging data architecture problem you faced and how you resolved it.

This question evaluates your problem-solving skills and ability to handle complex data scenarios.

How to Answer

Provide a specific example of a challenge you encountered, the steps you took to address it, and the outcome of your actions.

Example

“In a previous project, we faced performance issues with our data warehouse due to inefficient queries. I analyzed the query execution plans and identified several areas for optimization. By indexing key columns and restructuring the data model, we improved query performance by over 50%.”

4. How do you approach designing a data pipeline?

This question seeks to understand your methodology for creating efficient and scalable data pipelines.

How to Answer

Discuss the steps you take from requirements gathering to implementation, including any tools or technologies you prefer.

Example

“I start by gathering requirements from stakeholders to understand their data needs. Then, I design the pipeline architecture, selecting appropriate tools like Apache Kafka for real-time data streaming and Azure Data Lake for storage. Finally, I implement the pipeline, ensuring it is scalable and maintainable.”

5. What programming languages are you proficient in, and how have you used them in your data engineering work?

This question assesses your technical proficiency and ability to write code for data manipulation and processing.

How to Answer

List the programming languages you are comfortable with and provide examples of how you have used them in your projects.

Example

“I am proficient in Python and SQL. I have used Python for data manipulation and analysis, leveraging libraries like Pandas and NumPy. For instance, I developed a Python script to automate data cleaning tasks, which reduced manual effort by 40%. I also use SQL extensively for querying and managing relational databases.”

Behavioral Questions

1. Describe a time when you had to work collaboratively with a team to achieve a goal.

This question evaluates your teamwork and communication skills.

How to Answer

Share a specific example of a project where collaboration was key, highlighting your role and contributions.

Example

“During a project to integrate multiple data sources, I collaborated with data scientists and analysts to understand their requirements. I facilitated regular meetings to ensure alignment and shared progress updates. This collaboration led to a successful integration that met all stakeholders' needs.”

2. How do you handle tight deadlines and pressure in your work?

This question assesses your ability to manage stress and prioritize tasks effectively.

How to Answer

Discuss your strategies for managing time and maintaining productivity under pressure.

Example

“I prioritize tasks based on urgency and impact, using project management tools like JIRA to track progress. When faced with tight deadlines, I communicate openly with my team to redistribute workloads if necessary. This approach has helped me consistently meet project deadlines without compromising quality.”

3. Can you give an example of a time you made a mistake in your work? How did you handle it?

This question evaluates your accountability and ability to learn from mistakes.

How to Answer

Be honest about a mistake you made, how you addressed it, and what you learned from the experience.

Example

“I once misconfigured a data pipeline, which led to incorrect data being loaded into our warehouse. Upon realizing the error, I immediately notified my team and worked to correct the configuration. I also implemented additional checks to prevent similar issues in the future, which improved our overall data quality.”

4. What motivates you to work in data engineering?

This question seeks to understand your passion for the field and what drives you professionally.

How to Answer

Share your enthusiasm for data engineering and how it aligns with your career goals.

Example

“I am passionate about data engineering because it allows me to solve complex problems and make data accessible for decision-making. I find it rewarding to build systems that empower organizations to leverage data effectively, and I am excited about the continuous learning opportunities in this rapidly evolving field.”

5. How do you stay updated with the latest trends and technologies in data engineering?

This question assesses your commitment to professional development and staying current in your field.

How to Answer

Discuss the resources you use to keep your skills sharp and your knowledge up to date.

Example

“I regularly follow industry blogs, attend webinars, and participate in online courses to stay informed about the latest trends in data engineering. I also engage with the data engineering community on platforms like LinkedIn and GitHub to share knowledge and learn from others.”