Sr. Data Engineer - Supply Chain Analytics

About the job:

Sanofi is a global life sciences company committed to improving access to healthcare and supporting the people we serve throughout the continuum of care. From prevention to treatment, Sanofi transforms scientific innovation into healthcare solutions, in human vaccines, rare diseases, multiple sclerosis, oncology, immunology, infectious diseases, diabetes and cardiovascular solutions.

As a company with a global vision of drug development and a highly regarded corporate culture, Sanofi is recognized as one of the best pharmaceutical companies in the world and is pioneering the application of Artificial Intelligence (AI) with strong commitment to develop advanced data standards to increase reusability & interoperability and thus accelerate impact on global health.

The Global M&S Services acts as a cornerstone to this effort. Our team is responsible for delivering and supporting Global M&S teams in the area of regulatory compliance, maintenance of product licenses and technical writing of CMC documents. The team members of the global M&S Services Hub will act as partners in carrying out tasks and fulfilling responsibilities to support global quality activities with a focus on technical writing.

Main Responsibilities:

• Data Pipeline Development - Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver supply chain data from multiple sources (ERP, IBP, operational systems) using Python, SQL, dbt, and Airflow.
• Data Modelling & Architecture - Develop and optimize data models in Snowflake to support supply chain KPIs
• Analytics Enablement - Power BI dashboards understanding and self-service reporting solutions for supply chain stakeholders across global markets.
• Data Quality & Governance - Implement data quality checks, monitoring, and lineage tracking to ensure accuracy and reliability of supply chain data assets.
• Collaboration & Stakeholder Engagement - Partner with supply chain planners, SAP experts, and product owners to understand requirements and deliver impactful data solutions.
• Continuous Improvement - Identify opportunities to optimize existing pipelines, reduce latency, and improve data availability for business decision-making.
• Documentation - Maintain clear technical documentation for data pipelines, models, and processes.

About you:

• Experience: 7 to 10 years of experience in data engineering, with a strong focus on supply chain or operations analytics.
• Technical Skills: Advanced proficiency in Python and SQL Hands-on experience with Snowflake (data modelling, performance tuning, query optimization)
• Experience building and managing workflows with Apache Airflow or equivalent orchestration tools - intermediate
• Supply Chain Domain Knowledge - Good to have understanding of supply chain processes including demand planning, inventory management, logistics, and S&OP/IBP cycles.
• Data Architecture - Experience designing scalable data architectures (data lakes, data warehouses, medallion architecture).
• Education - Bachelor's or master's degree in computer science, Engineering, Data Science, or a related field.