omar-gamal99/talabat_bootcamp
May 2025 – May 2025
1 Month active
Languages Used
PythonYAML
Technical Skills
AirflowBigQueryCloud Data TransferDAG orchestrationData EngineeringETL
abdullaheldamanhoury
PROFILE
Abdullaheldamanhoury
During May 2025, Omar Gamal developed scalable data engineering solutions in the omar-gamal99/talabat_bootcamp repository, focusing on robust ETL pipeline design and orchestration. He built a reusable Airflow framework, including a starter DAG and a dynamic YAML-driven DAG factory, enabling configurable and maintainable pipeline generation. Leveraging Python and YAML, Omar delivered an end-to-end Orders ETL pipeline that extracts data from PostgreSQL, exports it as JSON to Google Cloud Storage, and loads it into BigQuery with overwrite logic and downstream triggers for cleaning and reporting. The work demonstrated depth in Airflow orchestration and cloud data integration, with incremental stability improvements.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
3
Lines of code
568
Activity Months1
Your Network
22 people
Work History
May 2025
12 Commits • 3 Features
May 1, 2025May 2025 monthly summary for omar-gamal99/talabat_bootcamp focused on delivering scalable data pipelines and establishing a reusable Airflow framework. Key features delivered include a starter Hello Airflow DAG, a complete Orders data ETL pipeline that moves data from PostgreSQL to Google Cloud Storage (as JSON) and into BigQuery with overwriting, plus downstream orchestration for cleaning and reporting. A Dynamic YAML-driven DAG factory was introduced to enable configurable, scalable pipeline generation. No major bugs were reported this month; however, several small refinements and stability improvements were executed across the ETL components.
12 Commits • 3 Features
May 1, 2025May 2025 monthly summary for omar-gamal99/talabat_bootcamp focused on delivering scalable data pipelines and establishing a reusable Airflow framework. Key features delivered include a starter Hello Airflow DAG, a complete Orders data ETL pipeline that moves data from PostgreSQL to Google Cloud Storage (as JSON) and into BigQuery with overwriting, plus downstream orchestration for cleaning and reporting. A Dynamic YAML-driven DAG factory was introduced to enable configurable, scalable pipeline generation. No major bugs were reported this month; however, several small refinements and stability improvements were executed across the ETL components.
May 2025
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance83.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
AirflowBigQueryCloud Data TransferDAG orchestrationData EngineeringETLGCSGoogle Cloud PlatformGoogle Cloud StoragePostgreSQLPythonYAML
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