Data Engineering
Advanced
Advanced
course description
The Data Engineering Track at GBG Academy is designed to take learners from core data fundamentals to building real, end-to-end data platforms used in modern organizations. The track combines strong conceptual foundations with hands-on practice, covering how data is collected, transformed, modeled, and delivered for analytics and decision-making. Learners gain practical experience building reliable, scalable data pipelines across on-premises and cloud environments. The program emphasizes real-world scenarios, industry-standard tools, and best practices, preparing learners to think and work like professional data engineers.
course outcomes
Data engineering foundations
Advanced SQL transformations
Design analytical models
Build ETL pipelines
Create analytics-ready datasets
Deliver end-to-end pipelines
Curriculum
Module 1: Introduction to Data Engineering
Introduces the data engineering role, core concepts, and environment setup, providing a clear overview of modern data platforms.
Module 2: SQL & Python Foundations
Covers SQL fundamentals and exploratory data analysis using Python, enabling learners to query, explore, and prepare data effectively.
Module 3: Data Modeling
Focuses on designing analytical data models, covering modeling techniques used to support reporting and decision-making.
Module 4: ETL with SSIS
Introduces ETL concepts using SQL Server Integration Services, focusing on building structured data pipelines.
Module 5: Advanced ETL Concepts
Covers incremental loading, data validation, and deployment strategies for building reliable and maintainable ETL processes.
Module 6: Analytical Models
Explores analytical modeling using SSAS and Tabular Editor, including row-level security for governed data access.
Module 7: Power BI
Covers data visualization and reporting using Power BI, focusing on building interactive dashboards and insights.
Module 8: On-Prem Data Engineering Project
Applies on-premises data engineering concepts through a hands-on project and structured review.
Module 9: Microsoft Fabric
Introduces Microsoft Fabric, covering ETL, semantic models, Power BI integration, and an end-to-end Fabric project.
Module 10: AWS Cloud Data Engineering
Covers cloud-based data engineering using AWS services, including S3, Glue, Redshift, and QuickSight, culminating in an end-to-end cloud data pipeline.
Instructor
Mustafa Gamal
Senior Data & AI Engineer
Mustafa Gamal is a Senior Data and AI Engineer and instructor at GBG Academy with strong expertise in cloud platforms, data engineering, and analytics. He brings hands-on experience designing scalable data architectures and delivering actionable insights. Mustafa equips learners with practical, industry-relevant skills using tools such as AWS, Azure, Python, and Power BI, and is passionate about enabling professionals to leverage data-driven technologies for impactful decision-making.
Fady Amr
Data Engineer
Fady Amr is a Data Engineer specializing in data warehousing, dimensional modeling, and ETL/ELT pipelines using the Microsoft data platform. He has strong experience building scalable data architectures, high-performance semantic models, and analytics solutions using Microsoft Fabric, SQL, and Power BI. Fady focuses on clean architecture, performance optimization, and maintainable data solutions that transform raw data into reliable, business-driven insights.