Building end-to-end business intelligence solutions with Power BI, SQL, and Python — backed by a solid AI & machine learning engineering background.
About
I am a Data Analyst and BI Developer with a background in AI engineering, combining analytical thinking with hands-on technical depth across the full data lifecycle.
I recently completed ITI's Power BI Development Track — a highly competitive 5-month program where I built end-to-end business intelligence solutions, from data modeling and DAX to interactive dashboards and automated reporting pipelines.
Before focusing on analytics, I worked as an AI Engineer on Automatic Speech Recognition systems and Computer Vision projects — experience that gives me a deeper understanding of data pipelines, model outputs, and what it takes to turn raw data into reliable decisions.
I hold a Bachelor's degree in Computer Engineering from Mansoura University (90.91%, Honors) and bring hands-on experience with Power BI, SQL Server, Python, and machine learning workflows.
Skills
Projects
End-to-end business intelligence system for Egyptian restaurant businesses. Covers data modeling, ETL pipelines, a Galaxy Schema data warehouse, 20 interactive dashboards, SSRS reports, and a real-time COD risk automation pipeline with Telegram alerts via n8n.
4-page Power BI dashboard analyzing employee attrition and performance across 1,470 employees. Built with Star Schema data modeling, role-playing relationships, and USERELATIONSHIP() in DAX.
3-dashboard Tableau project covering product, customer, and regional sales analysis. Features dynamic Top N filtering, drill-down hierarchy, geographic map, and dashboard navigation actions. Published on Tableau Public.
Multilingual (Arabic + English) purchase order categorization system built without external NLP libraries. Cleaned a 3,150-row dataset, explored 3 categorization approaches, and delivered a business recommendation with documented trade-offs.
Click-to-track system using YOLOv12 + OpenCV CSRT tracker. Supports mouse-click object selection, auto re-detection on tracking loss (confidence ≥ 0.7), and smallest-box selection for overlapping detections.
Hygiene violation detection system for pizza stores built as 5 microservices with Kafka, FastAPI, Streamlit, and Docker. Detects hygiene violations (missing scooper use) in real-time video streams.
Work Samples
Contact
Open to Data Analyst, BI Developer, and AI/ML Engineer opportunities — remote, hybrid, or on-site in Egypt and the Gulf region.