Join Wavestone, an international consulting firm, as part of the AI & Data practice. This is a hybrid role based in Puteaux, France. You will join a team of about 200 Data & AI consultants helping organizations transform end to end with AI. The role focuses on designing and industrializing data & AI platforms: defining and implementing modern data architectures (data lake / lakehouse, data warehouse, data mesh, data products) to support analytics, ML and GenAI; building robust data pipelines (batch, micro-batch, streaming) from ingestion to exposure (BI, APIs, ML features, and RAG). You will industrialize AI, GenAI and BI use cases by working with Data Scientists / AI Engineers to move from PoC to production, packaging models, automating workflows and applying MLOps / LLMOps best practices; designing and operating GenAI components (RAG pipelines, vector databases, LLM observability, prompts management, securing model calls). Contribute to data & AI platforms by collaborating with client Data & AI Platform teams (Data Platform Engineers, DevOps, Architects, Security) to define architecture patterns, tooling (Databricks, Snowflake, Dataiku, Azure / AWS / GCP) and development standards; serve as Tech Lead Data Engineering within AI squads, guiding technical scope, architecture decisions and code reviews, while mentoring developers. Ensure data quality, governance and observability across pipelines (data tests, monitoring, schema management, data contracts) and contribute to governance activities (catalogs, lineage, access security, AI Act compliance). Deploy agent-based soluti

Join Wavestone, an international consulting firm, as part of the AI & Data practice. This is a hybrid role based in Puteaux, France. You will join a team of about 200 Data & AI consultants helping organizations transform end to end with AI. The role focuses on designing and industrializing data & AI platforms: defining and implementing modern data architectures (data lake / lakehouse, data warehouse, data mesh, data products) to support analytics, ML and GenAI; building robust data pipelines (batch, micro-batch, streaming) from ingestion to exposure (BI, APIs, ML features, and RAG). You will industrialize AI, GenAI and BI use cases by working with Data Scientists / AI Engineers to move from PoC to production, packaging models, automating workflows and applying MLOps / LLMOps best practices; designing and operating GenAI components (RAG pipelines, vector databases, LLM observability, prompts management, securing model calls). Contribute to data & AI platforms by collaborating with client Data & AI Platform teams (Data Platform Engineers, DevOps, Architects, Security) to define architecture patterns, tooling (Databricks, Snowflake, Dataiku, Azure / AWS / GCP) and development standards; serve as Tech Lead Data Engineering within AI squads, guiding technical scope, architecture decisions and code reviews, while mentoring developers. Ensure data quality, governance and observability across pipelines (data tests, monitoring, schema management, data contracts) and contribute to governance activities (catalogs, lineage, access security, AI Act compliance). Deploy agent-based soluti