Atos Data Engineer Interview Questions + Guide in 2025

Atos is a global leader in data-driven, trusted, and sustainable digital transformation, operating in over 47 countries with a diverse portfolio of advanced computing and security solutions.

The Data Engineer role at Atos involves designing and implementing data solutions that meet business needs, with a strong focus on data architecture and modeling. Key responsibilities include analyzing business requirements and translating them into robust data models, developing best practices for data coding, and ensuring consistency across data systems. Ideal candidates should have significant experience (typically 10+ years) in data architecture, particularly within enterprise data warehouses, and be proficient in tools like Teradata and Power Designer. Understanding data profiling, ETL mapping, and optimizing data query performance are also crucial. Strong communication skills are essential, as the role requires collaboration with various stakeholders to drive data strategies and improve data workflows.

This guide will help you prepare thoroughly for your interview by focusing on the specific skills and experiences that Atos values in its Data Engineers, enabling you to present yourself as a well-rounded candidate.

The interview process for a Data Engineer position at Atos is structured and typically involves multiple stages to assess both technical and interpersonal skills.

1. Application and Initial Screening

The process begins with an online application, which is followed by an initial screening call with a recruiter. This call usually lasts around 30 minutes and focuses on your resume, professional background, and motivation for applying to Atos. The recruiter will also gauge your fit for the company culture and the specific role.

2. Technical Interview

Following the initial screening, candidates typically undergo a technical interview. This may be conducted via phone or video call and focuses on your technical expertise, particularly in data architecture, data modeling, and relevant tools such as SQL and Google Big Query. Expect questions that assess your understanding of data strategies, ETL mapping, and your experience with data profiling and integration.

3. Managerial and Behavioral Interview

The next step often involves a managerial or behavioral interview, where you will meet with a hiring manager or team lead. This round assesses your problem-solving abilities, leadership qualities, and how you handle project-related challenges. Questions may revolve around your past experiences, particularly in managing data projects and collaborating with cross-functional teams.

4. Client Interview

In some cases, candidates may also have a client interview, especially if the role involves direct client interaction. This round evaluates your communication skills and ability to articulate complex data concepts to non-technical stakeholders. You may be asked to discuss how you would approach client requirements and data solutions.

5. Final HR Round

The final stage is typically an HR round, which may include discussions about salary expectations and benefits. This round is also an opportunity for you to ask any remaining questions about the company culture, team dynamics, and career growth opportunities within Atos.

Throughout the process, it is essential to demonstrate not only your technical skills but also your ability to communicate effectively and work collaboratively in a team environment.

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

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

Understand the Role and Its Requirements

Before your interview, take the time to thoroughly understand the responsibilities and expectations of a Data Engineer at Atos. Familiarize yourself with data architecture, data modeling, and the specific tools mentioned in the job description, such as Teradata and Google Big Query. This knowledge will allow you to tailor your responses to demonstrate how your experience aligns with the role.

Prepare for Technical Questions

Expect a range of technical questions that assess your knowledge of data modeling, ETL processes, and data architecture. Be ready to discuss your experience with conceptual, logical, and physical data models, as well as your proficiency in SQL. Practicing common data engineering scenarios and problems can help you articulate your thought process clearly during the interview.

Highlight Your Problem-Solving Skills

Atos values candidates who can analyze and translate business needs into effective data solutions. Prepare to discuss specific examples from your past experience where you successfully identified problems, proposed solutions, and implemented data strategies. Use the STAR (Situation, Task, Action, Result) method to structure your responses, making it easier for interviewers to follow your thought process.

Communicate Clearly and Effectively

Strong communication skills are essential for a Data Engineer at Atos, as you will need to articulate complex technical concepts to various stakeholders. Practice explaining your past projects and technical concepts in a clear and concise manner. Be prepared to answer questions about how you would communicate data strategies and findings to non-technical team members.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your fit within the company culture. Atos values collaboration and teamwork, so be prepared to discuss how you have worked effectively in teams, managed conflicts, and contributed to a positive work environment. Reflect on your past experiences and think of examples that showcase your interpersonal skills and adaptability.

Prepare for Salary Negotiation

Salary negotiation is a key part of the interview process at Atos. Research industry standards for Data Engineers with your level of experience and be prepared to discuss your salary expectations confidently. Know your worth and be ready to justify your request based on your skills and the value you bring to the organization.

Follow Up After the Interview

After your interview, send a thank-you email to express your appreciation for the opportunity to interview. This not only shows your professionalism but also reinforces your interest in the position. Use this opportunity to briefly reiterate your enthusiasm for the role and how you can contribute to Atos.

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

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Atos. The interview process will likely focus on your technical skills, experience with data architecture, and your ability to translate business needs into effective data solutions. Be prepared to discuss your past projects, technical knowledge, and how you approach problem-solving in data engineering.

Technical Skills

1. Can you explain your experience with data modeling and the different types of data models you have worked with?

Understanding data modeling is crucial for a Data Engineer. Be ready to discuss your familiarity with conceptual, logical, and physical data models.

How to Answer

Highlight specific projects where you developed data models and the tools you used. Discuss the importance of each type of model in the context of your work.

Example

“In my previous role, I developed both logical and physical data models for an enterprise data warehouse using Teradata. I utilized Power Designer to create these models, ensuring they aligned with business requirements and optimized for performance.”

2. Describe a time when you had to implement a data strategy. What steps did you take?

This question assesses your strategic thinking and implementation skills in data engineering.

How to Answer

Outline the steps you took to analyze the business needs, design the data strategy, and implement it. Mention any challenges faced and how you overcame them.

Example

“I was tasked with implementing a data strategy for a new product line. I started by gathering requirements from stakeholders, then designed a data flow that integrated various data sources. I faced challenges with data quality, which I addressed by implementing data profiling techniques to ensure accuracy.”

3. How do you ensure data consistency and integrity in your projects?

Data consistency and integrity are vital in data engineering roles.

How to Answer

Discuss the best practices you follow, such as data validation, ETL processes, and monitoring.

Example

“I ensure data consistency by implementing strict validation rules during the ETL process. I also regularly monitor data quality metrics and conduct audits to identify and rectify any discrepancies.”

4. What is your experience with SQL and Google Big Query? Can you provide an example of a complex query you wrote?

SQL proficiency is essential for a Data Engineer, especially in handling large datasets.

How to Answer

Share your experience with SQL and any specific projects where you utilized Google Big Query. Provide a brief overview of a complex query you wrote.

Example

“I have extensive experience with SQL, particularly in Google Big Query. For instance, I wrote a complex query that joined multiple tables to generate a comprehensive report on customer behavior, which involved using window functions and subqueries to analyze trends over time.”

5. Can you explain the ETL process and your role in it?

Understanding the ETL process is fundamental for a Data Engineer.

How to Answer

Describe the ETL process and your specific contributions to it, including any tools you used.

Example

“In my last project, I was responsible for the ETL process where I extracted data from various sources, transformed it to meet business requirements, and loaded it into our data warehouse. I used tools like Apache NiFi for data extraction and transformation, ensuring the data was clean and structured for analysis.”

Problem-Solving and Project Management

6. Describe a challenging data integration project you worked on. What was your approach?

This question evaluates your problem-solving skills and ability to manage complex projects.

How to Answer

Discuss the project, the challenges you faced, and the steps you took to resolve them.

Example

“I worked on a data integration project that involved merging data from multiple legacy systems into a new data warehouse. The challenge was ensuring data compatibility and integrity. I conducted a thorough analysis of the source data, developed a detailed mapping document, and implemented a phased approach to integration, which minimized disruptions.”

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

Time management and prioritization are key skills for a Data Engineer.

How to Answer

Explain your approach to prioritizing tasks, including any tools or methodologies you use.

Example

“I prioritize tasks based on project deadlines and business impact. I use project management tools like JIRA to track progress and ensure that I’m focusing on high-impact tasks first. Regular communication with stakeholders also helps me adjust priorities as needed.”

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

Effective communication is essential in a Data Engineer role.

How to Answer

Share a specific instance where you successfully communicated complex concepts and the methods you used.

Example

“I once had to explain the implications of a new data model to a group of marketing stakeholders. I used visual aids, such as diagrams and flowcharts, to illustrate the data flow and its impact on their campaigns, ensuring they understood the benefits without getting lost in technical jargon.”

9. What tools and technologies do you prefer for data profiling and analysis?

This question assesses your familiarity with industry-standard tools.

How to Answer

Mention the tools you have experience with and why you prefer them.

Example

“I prefer using tools like Talend for data profiling due to its user-friendly interface and robust capabilities. Additionally, I often use Python for data analysis because of its flexibility and the powerful libraries available for data manipulation.”

10. How do you handle data security and compliance in your projects?

Data security is a critical aspect of data engineering.

How to Answer

Discuss the measures you take to ensure data security and compliance with regulations.

Example

“I prioritize data security by implementing encryption for sensitive data and ensuring compliance with regulations like GDPR. I regularly review our data handling practices and conduct training sessions for the team to stay updated on best practices.”