khaled seif

Working in different area to deliver best practices in building and optimizing data pipelines. Have main responsibility in : -RAG-based Chatbot Project Working on building and maintaining a Retrieval-Augmented Generation (RAG) system for chatbots to serve different clients, Interacting with data science teams to deliver the most convenient accuracy for the indexer search using Azure cloud tools such as Azure Logic Apps, Azure Functions, and Azure Search Service. -Agentic AI Project: Part of an agentic AI team, developing intelligent agents that fetch data from applications, orchestrate workflows, move data to GCP, and automatically create tickets on Agile boards, enabling cross-cloud automation and operational efficiency.

Served as a Session Lead and Instructor for the Azure Data Engineer track, delivering comprehensive sessions on Azure tools, including Azure Data Lake, Azure Synapse, Azure Functions, Azure Cosmos DB, and SQL. Led interactive quizzes, guided participants through data modeling and architecture, and provided hands-on training to build expertise in designing and implementing end-to-end data solutions.

Driving the development and delivery of enterprise-grade data solutions within the financial sector, with a focus on growth management and revenue optimization. Leading a team to design, build, and maintain robust data pipelines leveraging Azure technologies, enforce stringent data quality standards, and establish or refine data models to support critical business objectives.

-Executing the ETL process and shaping the Data Warehouse. -Crafting pipelines for automated cleansing through Azure Databricks and Azure Synapse, and Designing the underlying data model/schema to align with functional and non-functional product requirements. -Establishing quality checks, validating the design, and adjusting the model to meet the changing needs of the business and product features.

A post graduate professional training program in Big Data.

Graduation Project: Sentimental analysis for Product tracking using twitter data.