Leidos Data Engineer Interview Questions + Guide in 2025

Leidos is a leading provider of IT services, focused on developing and sustaining complex data and technology infrastructures for various sectors, including defense and intelligence.

In the role of Data Engineer at Leidos, you will play a pivotal part in supporting the National Media Exploitation Center (NMEC) as part of the DOMEX Technology Platform. Your key responsibilities will include designing, implementing, maintaining, and monitoring data pipelines to facilitate both R&D prototypes and production requirements. In this fast-paced environment, you will work closely with cross-functional teams, including developers, product managers, and quality assurance engineers, to ensure seamless integration and functionality of data systems.

The ideal candidate for this role will possess extensive experience in data engineering, with a strong focus on database management, ETL/ELT pipeline design, and data integrity best practices. Proficiency in SQL and NoSQL databases, as well as familiarity with tools like Spark, Airflow, and Python, are crucial to your success. Additionally, Leidos values teamwork, innovation, and professional development, making it essential for candidates to demonstrate strong collaboration skills, enthusiasm, and a proactive work ethic.

This guide will help you prepare for your interview by providing insights into the skills and experiences that Leidos emphasizes, enabling you to confidently articulate your qualifications and align them with the company's mission and values.

The interview process for a Data Engineer position at Leidos is structured to assess both technical and interpersonal skills, ensuring candidates are well-suited for the collaborative and innovative environment of the company. The process typically includes several stages:

1. Initial Screening

The first step is a phone screening conducted by an HR representative. This initial conversation lasts about 30 minutes and focuses on your background, experience, and motivation for applying to Leidos. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role.

2. Technical Interview

Following the initial screening, candidates usually participate in a technical interview, which may be conducted via video call or in person. This interview typically lasts around 45 minutes to an hour and includes questions related to data engineering concepts, SQL, database management, and coding challenges. Expect to discuss your experience with ETL processes, data pipeline design, and relevant technologies such as Spark, Airflow, and various database systems.

3. Behavioral Interview

After the technical interview, candidates may have a behavioral interview with the hiring manager or a panel of team members. This round focuses on assessing your soft skills, teamwork, and problem-solving abilities. Questions may revolve around past experiences, how you handle challenges, and your approach to collaboration in a team setting. This interview is crucial for determining cultural fit within the Leidos team.

4. Final Interview

In some cases, a final interview may be conducted with senior management or additional technical leads. This round is often more in-depth and may include discussions about your long-term career goals, alignment with Leidos' mission, and how you can contribute to the team. It may also involve a review of your technical skills through practical exercises or case studies.

5. Offer and Background Check

If you successfully navigate the interview rounds, you may receive a job offer. Given the nature of the work at Leidos, candidates will undergo a background check and must possess or be able to obtain a TS/SCI security clearance.

As you prepare for your interview, be ready to discuss your technical expertise and past projects in detail, as well as your approach to teamwork and problem-solving.

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 Company Culture

Leidos values innovation, collaboration, and professional development. Familiarize yourself with their mission and the specific team you are applying to. Be prepared to discuss how your values align with theirs and how you can contribute to their goals. Showing enthusiasm for their work and a genuine interest in their projects can set you apart.

Prepare for Technical Questions

Given the emphasis on SQL, NoSQL, and various database technologies, ensure you are well-versed in these areas. Brush up on your knowledge of database design, ETL processes, and data pipeline management. Be ready to discuss your experience with specific technologies mentioned in the job description, such as Spark, Airflow, and Python. Practice coding problems and be prepared to explain your thought process clearly.

Showcase Your Problem-Solving Skills

During the interview, you may be asked to solve technical problems or discuss past projects. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Highlight your analytical skills and how you approach problem-solving in data engineering contexts. Be specific about the challenges you faced and the solutions you implemented.

Emphasize Collaboration and Communication

Leidos operates in a collaborative environment, so be prepared to discuss your experience working in teams. Share examples of how you have effectively communicated with cross-functional teams, including developers, product managers, and QA personnel. Highlight your ability to work independently while also being a team player.

Be Ready for Behavioral Questions

Expect questions about how you handle difficult situations, work under pressure, and resolve conflicts. Prepare examples that demonstrate your soft skills, such as adaptability, teamwork, and leadership. Leidos values candidates who can contribute positively to their team dynamics.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers about the team, projects, and company culture. This not only shows your interest in the role but also helps you assess if Leidos is the right fit for you. Inquire about the technologies they are currently using, the challenges they face, and how they measure success in their projects.

Follow Up with Enthusiasm

After the interview, send a thank-you email expressing your appreciation for the opportunity to interview. Reiterate your interest in the position and briefly mention how your skills align with the team's needs. This can leave a positive impression and keep you top of mind as they make their decision.

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

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Leidos. The interview process will likely assess your technical skills, problem-solving abilities, and your experience with data engineering practices. Be prepared to discuss your past projects, technical knowledge, and how you can contribute to the team.

Technical Skills

1. What programming languages are you most comfortable using?

This question aims to gauge your technical proficiency and familiarity with relevant programming languages.

How to Answer

Discuss the programming languages you have experience with, particularly those relevant to data engineering, such as Python, SQL, or any others mentioned in your resume.

Example

“I am most comfortable using Python for data manipulation and analysis, as well as SQL for database querying. I have also worked with Java in some of my previous projects, particularly in building ETL pipelines.”

2. What is the difference between stack and heap memory?

This question tests your understanding of memory management, which is crucial for efficient data processing.

How to Answer

Explain the fundamental differences between stack and heap memory, focusing on their usage and characteristics.

Example

“Stack memory is used for static memory allocation, where variables are stored in a last-in, first-out manner. In contrast, heap memory is used for dynamic memory allocation, allowing for more flexible memory usage but requiring manual management to avoid memory leaks.”

3. Can you explain the ETL process and its importance?

This question assesses your knowledge of data processing workflows.

How to Answer

Define ETL (Extract, Transform, Load) and explain its significance in data engineering.

Example

“ETL stands for Extract, Transform, Load, which is a process used to move data from various sources into a data warehouse. It is crucial because it ensures that data is cleaned, transformed into a usable format, and loaded efficiently for analysis.”

4. Describe your experience with SQL and NoSQL databases.

This question evaluates your database management skills.

How to Answer

Discuss your experience with both SQL and NoSQL databases, highlighting specific projects or tasks.

Example

“I have extensive experience with SQL databases like MySQL and PostgreSQL, where I have designed schemas and optimized queries. Additionally, I have worked with NoSQL databases like MongoDB for handling unstructured data in a project focused on real-time analytics.”

5. What are some best practices for maintaining data integrity?

This question tests your understanding of data quality and management.

How to Answer

Outline key practices that ensure data integrity throughout its lifecycle.

Example

“Best practices for maintaining data integrity include implementing validation rules, using transactions to ensure atomicity, and regularly auditing data for accuracy. Additionally, employing data profiling techniques helps identify and rectify inconsistencies.”

Data Engineering Practices

1. What tools have you used for data pipeline development?

This question assesses your familiarity with data engineering tools.

How to Answer

Mention specific tools and technologies you have used for building data pipelines.

Example

“I have used Apache Airflow for orchestrating complex data workflows and Apache Spark for processing large datasets. Additionally, I have experience with tools like Dagster and Prefect for managing data pipelines.”

2. How do you approach performance tuning in databases?

This question evaluates your ability to optimize database performance.

How to Answer

Discuss strategies you employ to enhance database performance.

Example

“I approach performance tuning by analyzing query execution plans, indexing frequently accessed columns, and optimizing database configurations. Regularly monitoring performance metrics also helps identify bottlenecks.”

3. Can you explain the concept of data modeling?

This question tests your understanding of structuring data for efficient access.

How to Answer

Define data modeling and its importance in database design.

Example

“Data modeling is the process of creating a conceptual representation of data structures and relationships. It is essential for ensuring that the database is designed to meet business requirements and allows for efficient data retrieval.”

4. Describe a challenging data engineering problem you faced and how you solved it.

This question assesses your problem-solving skills and experience.

How to Answer

Share a specific example of a challenge you encountered and the steps you took to resolve it.

Example

“In a previous project, I faced issues with slow query performance due to large data volumes. I analyzed the queries and identified that adding appropriate indexes significantly improved performance. I also partitioned the data to enhance query efficiency.”

5. What is your experience with cloud-based data solutions?

This question evaluates your familiarity with cloud technologies.

How to Answer

Discuss your experience with cloud platforms and services relevant to data engineering.

Example

“I have worked extensively with AWS, utilizing services like S3 for data storage and Redshift for data warehousing. I have also implemented data pipelines using AWS Glue for ETL processes.”

Behavioral Questions

1. Tell me about a time you had to work with a difficult team member.

This question assesses your interpersonal skills and teamwork.

How to Answer

Share a specific instance and how you handled the situation.

Example

“I once worked with a team member who was resistant to feedback. I scheduled a one-on-one meeting to discuss our project goals and listened to their concerns. By fostering open communication, we were able to collaborate more effectively.”

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

This question evaluates your time management skills.

How to Answer

Explain your approach to prioritizing tasks and managing deadlines.

Example

“I prioritize tasks based on project deadlines and the impact on overall project goals. I use project management tools to track progress and ensure that I allocate time effectively to meet all deadlines.”

3. Describe a time when you had to learn a new technology quickly.

This question assesses your adaptability and willingness to learn.

How to Answer

Share an example of a situation where you had to quickly acquire new skills.

Example

“When I joined a new project that required knowledge of Apache Kafka, I dedicated time to online courses and hands-on practice. Within a few weeks, I was able to contribute effectively to the team’s data streaming solutions.”

4. Why do you want to work at Leidos?

This question gauges your interest in the company and role.

How to Answer

Discuss what attracts you to Leidos and how it aligns with your career goals.

Example

“I am drawn to Leidos because of its commitment to innovation and collaboration in data engineering. I believe my skills and experience align well with the company’s mission, and I am excited about the opportunity to contribute to impactful projects.”

5. How do you handle tight deadlines?

This question evaluates your ability to work under pressure.

How to Answer

Explain your strategies for managing stress and meeting deadlines.

Example

“I handle tight deadlines by breaking down tasks into manageable steps and focusing on high-priority items first. I also communicate with my team to ensure we are aligned and can support each other in meeting our goals.”