1 day ago
Paris, FranceSenior
Responsibilities
- Develop and operate data engineering frameworks, reusable components, templates, and best practices for AI-ready Data Products.
- Extend data engineering frameworks to enable AI agents to discover and consume Data Products at scale.
- Build AI assistants that accelerate Data Product development and operations.
- Collaborate with product owners, technical leads, and agile team members on technical design and incremental delivery.
- Set up and operate robust pipelines at scale.
Requirements
- Successful data engineering experience building enterprise-quality Data Products, preferably using Lakehouse architecture.
- Proficiency in Python development.
- Proficiency with version control systems such as GitHub and CI/CD frameworks such as GitHub Actions.
- Hands-on experience with Databricks, PySpark, and Delta Lake.
- Proficient written and spoken English for collaboration with international teams.
- Knowledge of and interest in Agentic AI, including familiarity with frameworks such as LangGraph.
- Experience with industry-standard technologies including Kubernetes and Docker.
Benefits
- Flexible working models and a culture focused on inclusion, health, and well-being.
- International team environment with opportunities to influence SAP product development and strategy.
- Location: Paris Levallois – Rue d’Alsace.
- Accessibility accommodations are available for applicants who need assistance during the application process.
Tech Stack
Categories
AI ApplicationsData Engineering
About SAP
SAP builds enterprise application software and cloud services for finance, procurement, supply chain, human resources, and analytics, sold through subscriptions, licenses, and support. Its portfolio includes SAP S/4HANA, SAP Business Technology Platform, SAP Ariba, and SAP SuccessFactors. Founded in 1972 and headquartered in Walldorf, Germany, SAP is a public company listed on the NYSE and Frankfurt (ETR) and serves enterprises and public-sector organizations worldwide.