omar-gamal99/talabat_bootcamp
May 2025 – May 2025
1 Month active
Languages Used
PythonYAML
Technical Skills
API IntegrationAirflowBigQueryCloud StorageCloud Storage ConfigurationDAG orchestration
Asmaa
PROFILE
Asmaa
Contributed to the omar-gamal99/talabat_bootcamp repository by building foundational data and API infrastructure for the Asmaa project, focusing on scalable analytics pipelines and client-facing APIs. Developed and enhanced Airflow DAGs to orchestrate reliable ETL workflows, integrating PostgreSQL data with BigQuery to support advanced analytics. Initiated both the Core Asmaa and Orders modules, while implementing a versioned API surface tightly coupled with BigQuery. Used Python and YAML to script data engineering solutions, leveraging Google Cloud Platform services for storage and orchestration. Ongoing work included DAG improvements, variant groundwork, and targeted cleanup, establishing a robust platform for future feature expansion and maintenance.
Overall Statistics
Feature vs Bugs
91%Features
Repository Contributions
27Total
Bugs
1
Commits
27
Features
10
Lines of code
362
Activity Months1
Your Network
22 peopleWork History
May 2025
27 Commits • 10 Features
May 1, 2025May 2025 monthly summary for the Asmaa project: Delivered foundational data and API capabilities with a focus on scalable analytics pipelines and client-ready APIs. Key outcomes include Airflow DAG enhancements for reliable workflows, PostgreSQL-to-BigQuery data integration to enable analytics, initialization of the Core Asmaa module and the Orders module, and a versioned API surface with BigQuery integration (across v2, v3, v4, v6, v7). Ongoing maintenance included DAG improvements and targeted cleanup. The work establishes a solid data analytics foundation, accelerates feature delivery, and supports future variant/version releases.
27 Commits • 10 Features
May 1, 2025May 2025 monthly summary for the Asmaa project: Delivered foundational data and API capabilities with a focus on scalable analytics pipelines and client-ready APIs. Key outcomes include Airflow DAG enhancements for reliable workflows, PostgreSQL-to-BigQuery data integration to enable analytics, initialization of the Core Asmaa module and the Orders module, and a versioned API surface with BigQuery integration (across v2, v3, v4, v6, v7). Ongoing maintenance included DAG improvements and targeted cleanup. The work establishes a solid data analytics foundation, accelerates feature delivery, and supports future variant/version releases.
May 2025
Activity
Loading activity data...
Quality Metrics
Correctness85.2%
Maintainability86.6%
Architecture83.6%
Performance84.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
API IntegrationAirflowBigQueryCloud StorageCloud Storage ConfigurationDAG orchestrationData EngineeringDatabase ConnectionETLGCSGoogle Cloud PlatformGoogle Cloud StoragePostgreSQLPythonPython Scripting
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline