Preparation for this role requires a blend of deep technical mastery and a clear demonstration of leadership maturity. You should be prepared to discuss your past projects not just in terms of the code you wrote, but in terms of the architectural decisions you made and the business outcomes they enabled.

Role-related knowledge – You must demonstrate deep expertise in Snowflake, Python, and AWS. Interviewers will look for your ability to explain why you chose specific tools and how you maintain high standards for DataOps and MLOps.

Problem-solving ability – You will be evaluated on your structured approach to ambiguous challenges. When presented with a case study or architectural scenario, focus on modular design, scalability, and proactive monitoring.

Leadership – You need to show that you can set a technical vision and bring others along with you. Highlight your experience in mentoring junior engineers and your approach to fostering collaboration across cross-functional teams.

The interview process at Coders Connect is designed to be thorough, focusing on both your technical depth and your alignment with the fast-paced, innovative nature of their partner projects. You can expect a professional, structured progression that begins with an initial recruiter screen followed by technical assessments and stakeholder interviews.

Candidates should be prepared for a potential gap in communication between stages; however, maintaining a proactive follow-up schedule is standard professional practice. The process is rigorous, and you should treat every interaction as an opportunity to demonstrate your leadership and technical problem-solving skills.

This visual timeline illustrates the typical stages from application to final evaluation. Use this to pace your preparation, ensuring you have refreshed your knowledge of AWS and Snowflake before the technical deep-dives. Remember that the process can vary slightly based on the specific project requirements for Sanofi.

Architecture & Design

You will be judged on your ability to build systems that are not only functional but maintainable and secure.

Be ready to go over:

• Pipeline Orchestration – How you manage dependencies and failures in Airflow.
• Data Modeling – Your approach to building efficient Snowflake datamarts.
• Compliance – Designing for regulated environments where data lineage and security are paramount.

Example scenarios:

• "Design an architecture for a RAG-based AI agent that requires strict data privacy."
• "How would you migrate an legacy ETL process to a modern DBT-based pipeline?"

Operational Excellence (DataOps/MLOps)

This area evaluates your commitment to stability and automation.

Be ready to go over:

• CI/CD – Implementing automated testing and deployment for data models.
• Observability – Strategies for monitoring data quality in real-time.
• Infrastructure as Code – Your experience using Terraform to manage AWS resources.

Example scenarios:

• "How do you ensure reproducibility in your machine learning data pipelines?"
• "Describe a time you implemented a fix for a critical production data failure."

As a Lead Data Engineer, your primary objective is to own the data lifecycle for AI-powered workflows. You will spend your time collaborating with architects and software engineers to ensure the infrastructure supporting GenAI agents is robust and scalable.

You will act as a bridge between technical implementation and business goals. This involves translating high-level product requirements into actionable technical tasks for your team, while remaining hands-on with the implementation of Snowflake datamarts and Python-based automation scripts.

A strong candidate for this position should possess a balanced background in engineering and leadership.

• Must-have skills – Deep expertise in Snowflake, Airflow, DBT, Python, AWS, Terraform, and GitHub Actions. You must have 6–8 years of relevant experience.
• Nice-to-have skills – Prior experience in the healthcare or biopharma industry is highly preferred. Experience with Agentic AI systems will set you apart.
• Soft skills – Exceptional communication and mentorship abilities are essential for leading your team and managing stakeholder relationships.

Q: How long does the hiring process usually take? A: While timelines can vary, from the initial recruiter screen to the final decision, expect a process lasting several weeks. Stay engaged and don't hesitate to follow up if you haven't heard back within a reasonable timeframe.

Q: What differentiates successful candidates? A: Successful candidates demonstrate a "hands-on leader" profile—someone who can architect complex systems but is also willing to dive into code to solve critical issues.

Q: Is this role fully remote? A: The position is based in Paris, and while hybrid flexibility may exist, you should be prepared for in-person collaboration as part of the team culture.

Q: How important is industry experience? A: While not strictly mandatory, experience in regulated industries like healthcare is a significant advantage due to the specific compliance requirements of the work.

• Structure your answers: Use the STAR method (Situation, Task, Action, Result) to keep your answers concise and impactful.
• Prepare for the 'Why': Be ready to explain why you chose a specific tool over another—interviewers value informed architectural trade-offs.
• Stay current: Brush up on the latest trends in GenAI and RAG pipelines, as these are central to the projects you will be leading.

The Lead Data Engineer role at Coders Connect is a unique opportunity to shape the future of AI in a global enterprise setting. By focusing on your core technical strengths in Snowflake and AWS, while demonstrating the leadership maturity required to guide a team through complex, regulated projects, you will position yourself as a top-tier candidate.

Preparation is your greatest asset. Use these insights to refine your narrative and practice your technical explanations. You can find additional resources and insights on Dataford to continue your preparation. You have the skills to succeed—stay focused, be confident, and bring your best to the interview.

The salary information provided reflects the broad range for this senior-level role. Compensation will be commensurate with your years of experience, depth of technical expertise, and leadership history.