Nassim Lamari

Contexte : At STELLANTIS, drafting technical specifications and developing new data flows for the LTP (sales forecasts) and 4P (production management) applications to integrate them into Snowflake.

Tasks:

• Drafting technical specifications for the new data flows.

• Architected and implemented scalable data pipelines and integration solutions.

• Authored detailed technical specifications and re-engineered outgoing data flows to ensure seamless integration into Snowflake.

• Led the modeling of data warehouses and ETL development.

Technical Environment: Snowflake, Cloud Azure, Azure Data Factory, TM1, Github, Pandas, SQL, Python

Context: POC aimed at standardizing their clients' financial repository using generative AI.

Tasks:

• Engineered processes for data preparation, transformation, and standardization.

• Gathering requirements from the GenAI (China) and Finance (England) teams.

• Creation of RAG (Retrieval-Augmented Generation) models.

• Preprocessing and transformation of raw data.

Technical Environment: Azure OpenAI, Langchain, Flask, ChromaDB, Streamlit, Docker, Python, GitLab

Context: At L'Oréal, for the new AFPT application (calculation of transfer pricing for products leaving the hubs), I was primarily responsible for connecting the AFPT application with GCP.

Tasks:

• Creation of incoming/outgoing ETL data flows.

• Created a multi-application file & data lifecycle management system.

• Built a predictive machine learning module to solve iterative equations

• Facilitation of various Agile sessions and team management during UAT sessions.

• Creation of dashboards for data observability and data pipeline monitoring.

• Training of new joiners.

Technical Environment: GCP, BigQuery, Airflow, GCS, Flask, Paw, Git, PowerShell , Docker, TM1 ,Python , SQL