Accelerator - Data & AI Engineering - Paris

Le contenu du poste est libellé en anglais car il nécessite de nombreuses interactions avec nos filiales à l’international, l'anglais étant la langue de travail.

Note we have multiple positions open.

Job title: Data & AI Engineer 

Location: Paris, France  Hybrid 3 days on site 

About the Job 

We are a global biopharmaceutical company focused on human health. Our purpose is to find treatment to fight pain and ease suffering. We combine breakthrough science and advanced technology to develop life-changing medicines and vaccines. 

Digital & Data is at the heart of Sanofi. Our ambition is to be the leading digital healthcare platform to develop and deliver medicine faster, enable healthcare professionals to improve treatments, and help patients improve their health. Our scale, strong connections within health ecosystems across the world, and ability to leverage Sanofi's capabilities make us the best place to push the boundaries of medicine through technology. 

We are building Digital R&D products developing outstanding capabilities that will participate in new drug discovery together with scientists, in trial efficiency and cycle time reduction, leveraging Data Analytics and Artificial Intelligence. 

Main Responsibilities 

Design and implement end-to-end data pipelines that transform raw data into valuable insights, ensuring scalability and reliability in cloud environments  Develop and optimize data models with a focus on query performance and efficient workloads  Collaborate with cross-functional teams to translate business requirements into technical solutions, defining clear interface contracts between data products and applications  Ensure data quality, standardization, observability, and governance across systems, aligning with industry compliance standards and data privacy requirements  Automate data ingestion processes and monitoring systems to track operational KPIs, troubleshoot issues, and maintain pipeline health  Build and maintain ETL processes and machine learning workflows, providing clean AI-ready data for downstream applications  Actively contribute to transversal data engineering best practices, including design patterns, CI/CD integrations, containerized deployments, and participate in peer review of code and technical documentation 

You are a dynamic Data & AI Engineer interested in challenging the status quo to ensure the seamless creation and operation of the data pipelines that are needed for the enterprise data and analytics initiatives following industry standard practices and tools for the betterment of our global patients and customers. 

You are a valued influencer and leader who has contributed to making key datasets available to data scientists, analysts, and consumers throughout the enterprise to meet vital business use needs. You have a keen eye for improvement opportunities while continuing to fully comply with all data quality, security, and governance standards. 

About You 

Experience 

Proven track record in designing and implementing data pipelines and data warehouse solutions in cloud environments  Hands-on experience with data modeling, ETL/ELT processes, and pipeline orchestration in production settings  Experience working in cross-functional teams, translating business needs into technical solutions  Experience working within compliance (e.g.: quality, regulatory, data privacy, GxP) and cybersecurity requirements  Experience in the healthcare industry is a strong plus 

Soft Skills 

Collaborative mindset with strong problem-solving abilities  Self-motivated and able to take initiative in a fast-paced environment  Effective communication skills to work with both technical and business stakeholders 

Technical Skills 

Strong proficiency in SQL and data warehousing platforms (Snowflake preferred)  Hands-on experience with ETL tools (IICS or equivalent), data transformation tools (dbt preferred), and Python for data processing  Strong experience with cloud platforms (AWS preferred) including orchestration frameworks (Airflow preferred)  Advanced knowledge of CI/CD practices (GitHub Actions preferred), version control (Git), and infrastructure as code principles (Terraform preferred)  Experience in designing and implementing engineering patterns and technical standards  Good knowledge of logging and monitoring tools such as Datadog, Grafana  Familiarity with containerization (Docker) and container orchestration (Kubernetes/Openshift a plus)  Possessing relevant cloud certifi