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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data And ai Engineer H/F - **Company:** Sanofi Groupe - **Location:** Lyon, France (Remote available) - **Salary:** €48,000.0 - €72,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Artificial Intelligence, Airflow, Amazon Web Services, Software Quality, Code Review, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Software Design Patterns, DevOps, Github, Monitoring of Systems, Python (Programming Language), Standard Sql, DataOps, Systems Integration, Data Processing, Cloud Platform System, Data Ingestion, Snowflake, Git, Containerization, Information Technology, Machine Learning Operations, Terraform, Software Version Control, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://www.hellowork.com/fr-fr/emplois/82992569.html ## About the Role Experience: - Experience owning delivery of data pipeline workstreams and data warehouse solutions in cloud environments. - Hands-on experience improving data models, ETL/ELT processes, and pipeline orchestration in production settings. - Experience partnering with cross-functional teams to shape technical solutions and delivery plans. Technical Skills: - Confident SQL skills on modern data warehousing platforms (Snowflake preferred), including performance-aware design. - Hands-on experience building and improving ETL/ELT pipelines (IICS or equivalent), data transformation models (dbt preferred), and Python data processing components. - Experience operating cloud data services (AWS preferred) and orchestration frameworks (Airflow preferred) for production workflows. - Practical DevOps and DataOps experience, including CI/CD (GitHub Actions preferred), version control (Git), and infrastructure as code principles (Terraform preferred). - Ability to choose and apply engineering patterns and technical standards for defined workstreams. Soft Skills: - Owns delivery of defined data engineering workstreams with sound judgment, accountability, and attention to operational quality. - Partners confidently with cross-functional stakeholders to shape practical technical solutions. - Shares knowledge with peers and helps improve team practices through reviews and documentation. - Comfortable using approved AI-enabled tools to improve engineering productivity, documentation, code quality, and operational effectiveness, while following Sanofi's Responsible AI and data governance standards. - Patient-focused and quality-driven, with a collaborative mindset, high standards, and a constructive approach to feedback, problem-solving, and continuous improvement. Education:Bachelor'sorMaster'sdegreeinEngineering,Computer Science or a related field. Languages:English is mandatory ## Description Own delivery of defined data pipeline workstreams that transform raw data into valuable insights, ensuring scalability and reliability in cloud environments. - Develop, tune, and refactor data models with a focus on query performance, workload efficiency, and maintainability. - Partner with cross-functional teams to turn business requirements into technical solutions and delivery plans. - Implement data quality checks, apply governance standards, and drive clear remediation paths for quality issues. - Operate automated data ingestion, observability, and monitoring systems to track operational KPIs, troubleshoot issues, and improve pipeline health. - Build, maintain, and improve ETL processes and machine learning workflows, providing clean AI ready data for applications and downstream products. - Apply and share data engineering practices through design patterns, CI/CD integrations, containerized deployments, code reviews, and technical documentation. ## Related Videos - [Designing How Work Feels: The Science Behind Sanofi’s Workplace Experience](https://www.wearedevelopers.com/videos/1848-designing-how-work-feels-the-science-behind-sanofi-s-workplace-experience) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Best Companies to Work For in Paris: Top 25 Companies in 2023 ](https://www.wearedevelopers.com/magazine/190-best-companies-to-work-for-in-paris-top-25-companies-in-2023) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)