The questions you face at Alten are designed to spark conversation rather than test rote memorization. They will focus heavily on your practical experience and your ability to navigate client environments. The goal is to see how you think, communicate, and solve problems in the real world.

Past Projects and Architecture

These questions dominate the technical exchange with the Tech Lead. They want to understand your exact role in previous achievements.

• Walk me through the architecture of the data pipeline in your most recent project.
• What was the most challenging technical bug you resolved in your last mission?
• Why did your team choose [Specific Tool/Technology] over its alternatives?
• How did you ensure data quality and handle missing data in your previous pipelines?
• Describe a time when you had to optimize a slow-running query or data process.

Consulting and Behavioral Fit

Assessed primarily by the business and commercial managers, these questions test your readiness for client deployment.

• Give me a brief presentation of your background and your key strengths.
• How do you handle working with a client who has very vague or constantly changing requirements?
• Describe a situation where you had to quickly learn a new technology to complete a project.
• How do you manage disagreements regarding technical choices with a client's internal team?
• Why do you want to work in consulting, specifically at Alten?

Core Technical Concepts

These conversational questions ensure your fundamentals are strong enough to adapt to any client's tech stack.

• Explain the difference between ETL and ELT.
• How do you design a schema for a data warehouse?
• What are the main differences between relational and NoSQL databases, and when would you use each?
• Explain how partition and clustering work in distributed data systems.
• How would you approach migrating an on-premise database to the cloud?

Consulting and Client-Facing Skills

Since Alten is a consulting firm, your interactions with the business managers and commercial teams are critical. They are evaluating whether they can confidently place you in front of a major client. Strong performance in this area means projecting confidence, demonstrating active listening, and showing a willingness to adapt to different corporate cultures.

Be ready to go over:

• Stakeholder management – How you handle changing requirements or pushback from business users.
• Presentation skills – Your ability to introduce yourself concisely and professionally.
• Career mobility – Your willingness to learn new technologies or commute to various client sites.

Example questions or scenarios:

• "How do you handle a situation where a client's technical team disagrees with your proposed architecture?"
• "Present yourself and your background in three minutes, focusing on the value you bring to a data team."
• "Describe a time you had to explain a complex data issue to a non-technical stakeholder."

Core Data Engineering Concepts

While you may not face a live coding test, the technical exchange will probe your foundational knowledge. The Tech Lead will test your understanding of universal data engineering concepts to ensure you can adapt to various client stacks. Strong candidates can discuss the trade-offs between different technologies fluently.

Be ready to go over:

• ETL/ELT paradigms – Differences, use cases, and modern tooling (e.g., dbt, Airflow).
• Data modeling – Star schema, snowflake schema, and when to use NoSQL vs. relational databases.
• Cloud and Big Data ecosystems – General knowledge of AWS, GCP, or Azure data services, as well as distributed computing (Spark, Hadoop).

Example questions or scenarios:

• "How would you design a data warehouse from scratch for a retail client?"
• "Explain the difference between batch processing and stream processing, and when you would use each."
• "What are the key differences between a transactional database (OLTP) and an analytical database (OLAP)?"

Key Responsibilities

As a Data Engineer at Alten, your day-to-day work is highly dependent on your specific client assignment, but the core deliverables remain consistent. You will be responsible for designing, building, and maintaining scalable data pipelines that ingest raw data from various sources and transform it into actionable insights. This often involves working within a client's existing cloud infrastructure, optimizing legacy code, and migrating on-premise solutions to the cloud.

Collaboration is a massive part of the role. You will embed deeply with client teams, working alongside their internal Data Scientists, Software Engineers, and Product Managers. You will participate in Agile ceremonies, contribute to architectural discussions, and provide technical guidance. Because you are an external consultant, you are often expected to bring fresh perspectives and best practices to the client's data operations.

You will also be responsible for ensuring data quality and governance. This means writing robust tests for your pipelines, setting up monitoring and alerting systems, and ensuring compliance with data privacy regulations (like GDPR). Your ultimate goal is to build reliable, automated systems that allow the client's business units to make data-driven decisions seamlessly.

Role Requirements & Qualifications

To be a competitive candidate for the Data Engineer role at Alten, you need a solid technical foundation paired with the soft skills necessary for consulting.

• Must-have technical skills – Strong proficiency in SQL and at least one programming language (typically Python or Scala). Experience with building ETL/ELT pipelines and working with relational databases.
• Must-have soft skills – Excellent verbal and written communication. You must be able to present yourself professionally, articulate your past experiences clearly, and demonstrate high emotional intelligence for stakeholder management.
• Experience level – Typically, candidates need at least 2 to 5 years of hands-on data engineering experience. A proven track record of delivering end-to-end projects is highly valued.
• Nice-to-have skills – Hands-on experience with modern orchestration tools (like Apache Airflow), distributed computing frameworks (like Apache Spark), and cloud platforms (AWS, Azure, or GCP). Official cloud certifications are a significant bonus in the consulting world.