Libasse Dia

Management and optimization of the DataPlatform Technical Environment: Azure Data Factory, Java, Spark Streaming, AKS, PowerBI, Azure DevOps, SQL Server, DBT, Airflow Main missions: Data ingestion: implementation and monitoring of ingestion processes via Azure Data Factory. Development & maintenance: Java Spark Streaming flows, and monitoring of jobs on AKS Optimizations: work on indexes, compression, table structure, SQL query, and PowerBI dashboard updates CI/CD Deployment: creation of Azure DevOps pipelines for runbooks (Azure Automation) and

POC: demo of solutions with DBT + Airflow.

Data Engineer / Generative AI

Capgemini Internal, Paris

Development of GenAI Use Cases Technical Environment: Azure OpenAI, Azure Cognitive Search, LangChain, Python, Streamlit Main missions: Backend Devs: Python programming. Vectorization: building vectorStore with Azure Cognitive Search. Specific Use Cases: Chatbot + prompt (Azure OpenAI, LangChain) RetroDoc and OCR (PDF, Excel, etc.) and Speech-to-Text Generation of letters and advertising scenarios Workshops: leading sessions with clients and internal teams. Interface: using Streamlit.

Project for consolidation in Snowflake (Data Mesh) Technical Environment: Snowflake, DBT Cloud, Snowpipes, Jenkins, Git, SQLFluff Linter Main missions: Initialization: DBT models for Casino and Poker departments, connecting DBT Cloud to Snowflake. Data ingestion: S3 + snowpipe for file integration. Performance monitoring: monitoring metrics (execution time), managing auto-resume/auto-suspend parameters. Data management: Dynamic Data Masking, access control, and data sharing. Transformation: data historization (bronze) and transformation into business data (silver) via Data Vault modeling. CI/CD: Jenkins + Git, adherence to SQLFluff rules.