About
We are Pierre Fabre Laboratories, a global leader combining pharmaceutical expertise with dermo-cosmetics to support consumers and patients at every stage of their care journey. Our portfolio includes several medical franchises and international brands such as Eau Thermale Avène, Ducray, A-Derma, Klorane, René Furterer, and Pierre Fabre Oral Care. Present in 120 countries with a team of over 10,000 employees.
Responsibilities
•Define, develop, set up and ensure the maintenance of infrastructures and collection and storage tools to allow a smooth analysis of the data by the Data Science / Data analysis teams
•Design, test, document and implement data solutions / architectures to allow large volumes of internal or external data sources to be processed
•Apply security rules to useful data sources, make them accessible if necessary
•Organize flows from sources to storage bases
•Qualify the degree of confidence in the data
•Ensure its usability for Data Analysts and Data Scientists and interoperability between systems
•Ensure a permanent watch on the technologies and languages used in order to share knowledge and drive project progress
Requirements
•Significant experience in data engineering, including ownership of production-grade cloud data platforms and large-scale data pipelines
•Demonstrated experience leading and developing data engineers
•Strong experience with AWS and at least one modern data platform or lakehouse/warehouse ecosystem such as Databricks, Snowflake or SageMaker Unified Studio
•Advanced practical skills in SQL and Python, data modelling, ETL/ELT, orchestration, APIs and distributed data processing
•Experience with cloud object storage, open table/file formats, metadata, data quality, lineage and secure data access
•Experience implementing engineering practices including Git, CI/CD, infrastructure as code, automated testing, monitoring and incident management
•Ability to engage with scientific and business stakeholders, convert ambiguous needs into executable delivery plans and communicate technical trade-offs clearly
•Professional fluency in English; French is strongly valued
•Experience in pharmaceutical, biotechnology, healthcare or another regulated R&D environment
•Understanding of scientific and clinical data, including ELN/LIMS, instrument data, omics, preclinical, clinical or real-world data
•Experience supporting GxP workloads, GDPR, HDS or comparable regulated-data requirements
•Knowledge of FAIR principles, data products, semantic layers, master/reference data and federated data governance
•Experience operating across AWS and Azure boundaries and integrating SaaS platforms, partner data exchanges and streaming services
•Master's degree or equivalent experience in computer science, engineering, data or a related discipline
