Data Engineering Lead- R&D pharma- M/F - CDI

Pierre Fabre; Toulouse; Hybrid; EUR 110,000 - 150,000; Full time

Benefits offered by this job

Incentives

Profit-sharing

Shareholding with matching

Health insurance

Provident insurance

RTT 16 days + 25 personal days

Public transport participation

Job summary

Pierre Fabre recherche un Lead Data Engineering pour Toulouse, chargé de diriger l’équipe et de prendre la propriété technique de la plateforme data R&D. Vous concevrez et opérerez des pipelines cloud robustes, en collaboration avec la science des données, la biométrie et les équipes métiers, afin de délivrer des data produits conformes et évolutifs.

Le poste exige une expérience significative en data engineering, une maîtrise d’AWS et d’au moins une plateforme moderne

Qualifications

• Expérience avérée en data engineering et plateformes cloud de production.
• Gestion et développement d’équipes de data engineers.
• Maîtrise d’AWS et d’au moins une plateforme moderne (Databricks/Snowflake/SageMaker).
• Compétences avancées en SQL et Python, modélisation des données, ETL/ELT et orchestration.
• Connaissance des APIs, des pratiques CI/CD et du versioning Git.
• Anglais professionnel; le français est apprécié.

Responsibilities

• Diriger l’équipe Data Engineering et fixer les priorités.
• Assurer la propriété technique de la data plateforme R&D.
• Concevoir et livrer des data produits fiables pour R&D.
• Implémenter et faire évoluer le CI/CD, IaC et la qualité des données.
• Collaborer avec Scientifiques et Business pour traduire les besoins en livrables.

Skills

Data engineering leadership

AWS

Databricks

Snowflake

SageMaker Unified Studio

SQL

Python

ETL/ELT

Data modelling

APIs

Git

CI/CD

Infrastructure as Code

Education

Master en informatique/Ingénierie/Data

Tools

Databricks

Snowflake

SageMaker Unified Studio

AWS

SQL

Python

Git

CI/CD

Infrastructure as Code

Job description

# Votre missionPierre Fabre is accelerating its transformation toward a more digital, data-driven and AI-enabled R&D organization. To support this ambition, we are creating a new **Data Engineering Lead** position in Toulouse (Langlade, 31). You will be part of the R&D Data Engineering team that operates the data platform and delivers trusted, reusable data products for Data Science, Biometry and all other R&D functions. The role combines team leadership, technical ownership and hands-on delivery. It is accountable for turning fragmented scientific and operational data into governed, production-grade assets that accelerate R&D decisions and use cases.**Your role within a pioneering company in full expansion:** **1. Lead the Data Engineering team**· Build, organize and lead an internal team of data engineers, complemented by external partners when required.· Set clear priorities, allocate capacity and establish an explicit delivery backlog jointly with R&D stakeholders and Data Science leads.· Coach engineers, raise engineering standards, develop skills and create a culture of accountability, collaboration and continuous improvement. **2. Own data-platform engineering and operations**· Take technical ownership of the R&D data platform in its AWS landing-zone environment, from implementation through reliable day-to-day operation and evolution.· Define and enforce reference architectures, reusable patterns and engineering standards for ingestion, transformation, orchestration, storage and data serving.· Implement infrastructure as code, CI/CD, automated testing, environment separation, observability, incident response and disaster-recovery practices. **3. Deliver trusted data products for R&D**· Partner with scientists, Data Science, Biometry, Business Analysts and R&D domain teams to translate needs into prioritised data products and services.· Design, build and operate batch, incremental, API-based and event-driven pipelines across laboratory, preclinical, clinical, external-partner and operational sources.· Create curated, documented and reusable datasets with clear schemas, ownership, quality rules, access conditions, SLAs and lifecycle management.· Provide governed access through SQL, APIs, notebooks and other fit-for-purpose interfaces, enabling analytics, AI and scientific applications. **4. Embed quality, security and compliance by design**· Embed automated data-quality controls, lineage, metadata capture, auditability and reproducibility into engineering workflows.· Apply role-based and data-level access controls, encryption, retention and classification requirements in partnership with Security, Data Governance, Quality, Legal and the DPO.· Support GxP-qualified workloads, GDPR obligations and HDS-compliant EU data residency where required. **5. Shape the engineering roadmap and ecosystem**· Contribute to platform technology selection and lead the engineering roadmap from MVP to scale.· Evaluate and integrate relevant technologies across AWS and modern data platforms such as Databricks, Snowflake or SageMaker Unified Studio, based on the selected target architecture.· Ensure interoperability with the existing R&D estate, including Azure-hosted sources, GitHub, Veeva, electronic laboratory notebooks, statistical computing environments and external CRO/partner channels.This position is compatible with teleworking up to 2 days a week according to company rules.We offer an attractive remuneration/benefits package: Incentives, profit-sharing, Pierre Fabre shareholding with matching contribution, health and provident insurance, 16 days of holidays (RTT) in addition to 25 days of personal holidays, public transport participation...# Qui êtes-vous ?**Your skills at the service of innovative projects:** **Essential**· 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. **Preferred**· 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.*La première richesse des Laboratoires Pierre Fabre, sont les femmes et les hommes qui les composent* disait M. Pierre Fabre.Fiers de cet héritage, et convaincus que la diversité des parcours, des expériences et des identités renforce notre performance collective, nous nous engageons à promouvoir l’égalité des chances et à garantir un environnement inclusif pour tous. Dans le respect des lois en vigueur, toutes les candidatures sont étudiées avec la même attention, sans distinction d’origine, de sexe, d’âge, de situation de handicap, d’orientation sexuelle, d’identité de genre, de croyances ou de toute autre caractéristique protégée par la loi.