Harris IT Services Data Engineer Interview Questions + Guide in 2025

Harris IT Services is a leading national security company that provides innovative solutions to protect and serve government agencies and military operations.

The Data Engineer role is a critical position within the organization, responsible for designing, implementing, and maintaining robust data pipelines and systems that support mission-critical aviation operations. This role requires a deep understanding of data management, ETL processes, and database architectures, as well as experience with data integration and processing technologies. Key responsibilities include collaborating with cross-functional teams, ensuring data quality and integrity, optimizing data flows, and providing technical support for data-related challenges. A successful candidate will possess strong analytical skills, proficiency in programming languages such as Python and SQL, and a commitment to maintaining data security and compliance within a government context.

This guide aims to equip candidates with the knowledge and insights necessary to excel in interviews for the Data Engineer role at Harris IT Services. By understanding the specific skills and responsibilities involved, candidates can prepare effectively and present themselves as informed and capable professionals.

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

1. Initial Phone Screen

The first step is an initial phone interview, usually conducted by a recruiter. This conversation lasts about 30 minutes and focuses on your background, experience, and motivation for applying to Harris IT Services. The recruiter will also gauge your understanding of the role and the company culture, as well as your communication skills.

2. Technical Interviews

Following the initial screen, candidates typically undergo a series of technical interviews. These interviews are conducted by a panel of software engineers, often in three layers. Each session focuses on different aspects of data engineering, including data pipeline development, ETL processes, and database management. Expect to discuss your experience with tools and technologies relevant to the role, such as Python, SQL, and data processing frameworks. You may also be asked to solve technical problems or case studies that reflect real-world scenarios you might encounter in the position.

3. Interview with Hiring Manager

After the technical interviews, candidates will meet with the hiring manager. This interview is more focused on assessing your fit within the team and your ability to contribute to ongoing projects. The hiring manager will likely ask about your previous experiences, how you handle challenges, and your approach to collaboration with cross-functional teams.

4. Final HR Interview

The final step in the interview process is typically an interview with an HR recruiter. This session may cover topics such as salary expectations, benefits, and company policies. The HR representative will also assess your alignment with the company’s values and culture, ensuring that you are a good fit for the organization.

As you prepare for your interviews, it’s essential to be ready for a variety of questions that will test your technical knowledge and problem-solving abilities.

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

Understand the Interview Structure

Be prepared for a multi-layered interview process. You may encounter several technical interviews with software engineers, followed by a discussion with the hiring manager and an HR recruiter. Familiarize yourself with the types of questions that may be asked at each stage, and be ready to articulate your experience and skills clearly. It’s also important to prepare for behavioral questions that assess your fit within the company culture.

Showcase Your Technical Expertise

As a Data Engineer, you will need to demonstrate your proficiency in data pipeline development, ETL processes, and database management. Brush up on your skills in Python, PySpark, and SQL, as these are critical for the role. Be prepared to discuss specific projects where you have successfully designed and implemented data solutions, focusing on the challenges you faced and how you overcame them.

Emphasize Collaboration and Communication

Given the collaborative nature of the role, it’s essential to highlight your ability to work with cross-functional teams. Prepare examples that showcase your experience in collaborating with data scientists, analysts, and other stakeholders. Be ready to discuss how you’ve communicated complex technical concepts to non-technical team members, as this will demonstrate your ability to bridge the gap between technical and operational needs.

Align with Company Values

Research Peraton’s mission and values, particularly their focus on national security and innovative solutions. Be prepared to discuss why you want to work for Peraton and how your personal values align with the company’s mission. This will not only show your enthusiasm for the role but also your commitment to contributing to the company’s objectives.

Prepare for Security Clearance Discussions

Since this role requires a Top Secret/SCI clearance, be ready to discuss your eligibility and any previous experience you have with sensitive data. Understand the implications of working in a government context and be prepared to answer questions about your ability to handle confidential information responsibly.

Practice Problem-Solving Scenarios

Expect to encounter scenario-based questions that assess your problem-solving skills. Prepare to discuss how you would approach specific data engineering challenges, such as optimizing data pipelines or ensuring data quality. Use the STAR (Situation, Task, Action, Result) method to structure your responses, providing clear examples of your thought process and the outcomes of your actions.

Stay Current with Industry Trends

Demonstrating knowledge of emerging technologies and trends in data engineering will set you apart. Be prepared to discuss any recent advancements in data management, cloud technologies, or data security practices that you find relevant. This shows your commitment to continuous learning and your ability to adapt to the evolving landscape of data engineering.

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

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Harris IT Services. The interview process will likely focus on your technical skills, problem-solving abilities, and experience with data management and engineering practices. Be prepared to discuss your past projects, the technologies you've used, and how you approach data challenges.

Technical Skills

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

This question aims to assess your familiarity with Extract, Transform, Load (ETL) processes, which are crucial for data engineering roles.

How to Answer

Discuss specific ETL tools you have used, the types of data you have worked with, and any challenges you faced during the ETL process. Highlight your problem-solving skills and how you ensured data quality.

Example

“I have extensive experience with ETL processes using tools like Apache NiFi and Talend. In my previous role, I developed a pipeline that ingested data from various sources, transformed it to meet business requirements, and loaded it into a data warehouse. I faced challenges with data quality, which I addressed by implementing validation checks at each stage of the ETL process.”

2. What strategies do you use to ensure data quality and integrity?

This question evaluates your understanding of data quality principles and practices.

How to Answer

Explain the methods you employ to maintain data quality, such as validation, cleansing, and monitoring techniques. Provide examples of how you have implemented these strategies in past projects.

Example

“I prioritize data quality by implementing validation rules during the data ingestion phase and regularly monitoring data integrity through automated scripts. For instance, I developed a data quality dashboard that flagged anomalies in real-time, allowing us to address issues promptly.”

3. How do you approach designing a data pipeline?

This question assesses your design thinking and technical skills in building data pipelines.

How to Answer

Discuss the steps you take when designing a data pipeline, including understanding requirements, selecting appropriate technologies, and ensuring scalability and performance.

Example

“When designing a data pipeline, I start by gathering requirements from stakeholders to understand their needs. I then choose the right technologies, such as Apache Kafka for streaming data and AWS for storage. I ensure the pipeline is scalable by using modular components and implementing monitoring tools to track performance.”

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

This question tests your knowledge of database technologies, which is essential for a data engineer.

How to Answer

Provide a clear comparison of SQL and NoSQL databases, focusing on their use cases, strengths, and weaknesses.

Example

“SQL databases are relational and use structured query language for defining and manipulating data, making them ideal for complex queries and transactions. In contrast, NoSQL databases are non-relational and can handle unstructured data, making them suitable for big data applications where scalability and flexibility are crucial.”

5. Describe a challenging data-related problem you encountered and how you resolved it.

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

How to Answer

Share a specific example of a data challenge you faced, the steps you took to resolve it, and the outcome of your actions.

Example

“I once encountered a significant data inconsistency issue during a migration project. After identifying the root cause, which was due to mismatched data formats, I collaborated with the data owners to standardize the formats and implemented a validation process to prevent future occurrences. This not only resolved the issue but also improved our data governance practices.”

Collaboration and Communication

1. How do you collaborate with data scientists and analysts?

This question assesses your teamwork and communication skills, which are vital in a cross-functional environment.

How to Answer

Discuss your approach to collaboration, including how you share information, gather requirements, and support data analysis efforts.

Example

“I regularly collaborate with data scientists and analysts by holding joint meetings to discuss project goals and data requirements. I ensure that I provide them with clean, well-structured data and am always open to feedback to improve our data processes.”

2. Can you give an example of how you communicated complex technical concepts to non-technical stakeholders?

This question evaluates your ability to convey technical information clearly.

How to Answer

Share a specific instance where you successfully communicated complex ideas to a non-technical audience, focusing on your approach and the outcome.

Example

“In a previous project, I had to explain our data architecture to a group of non-technical stakeholders. I used visual aids and analogies to simplify the concepts, which helped them understand the importance of our data strategy. This led to better support for our initiatives and alignment on project goals.”

3. How do you handle feedback from team members or stakeholders?

This question assesses your receptiveness to feedback and your ability to adapt.

How to Answer

Discuss your approach to receiving feedback, how you incorporate it into your work, and any examples of positive changes resulting from feedback.

Example

“I view feedback as an opportunity for growth. For instance, after receiving input on my data visualization reports, I adjusted my approach to focus more on user experience, which significantly improved the reports' usability and stakeholder satisfaction.”

4. Describe a time when you had to work under tight deadlines. How did you manage your time?

This question evaluates your time management skills and ability to work under pressure.

How to Answer

Share a specific example of a project with a tight deadline, the strategies you used to manage your time, and the outcome.

Example

“During a critical project, I had to deliver a data pipeline within a week. I prioritized tasks by breaking the project into smaller milestones and used project management tools to track progress. By focusing on high-impact tasks first, I successfully delivered the pipeline on time, which was crucial for the project’s success.”

5. Why do you want to work with Harris IT Services?

This question assesses your motivation and alignment with the company’s mission and values.

How to Answer

Express your interest in the company and how your skills and values align with their goals. Mention specific aspects of the company that attract you.

Example

“I am drawn to Harris IT Services because of its commitment to national security and innovative data solutions. I believe my experience in data engineering and my passion for using data to drive decision-making align perfectly with your mission to support government operations effectively.”