Ready-Talent/data-engineering-d25
Nov 2024 – Nov 2024
1 Month active
Languages Used
PythonSQLYAML
Technical Skills
AirflowBigQueryData EngineeringData ModelingETLGoogle Cloud Platform
Menna Hassanin
PROFILE
Menna Hassanin
During November 2024, Menna Hassanin developed and refined an end-to-end data pipeline within the Ready-Talent/data-engineering-d25 repository, enabling automated data movement from PostgreSQL to BigQuery via Google Cloud Storage in CSV format. She implemented dynamic path resolution and robust schema handling using Airflow and Python, ensuring data integrity and cross-platform compatibility. Menna also initiated a dbt project to establish analytics modeling, testing workflows, and schema governance, laying the groundwork for scalable analytics. Her work centralized query-ready data in BigQuery, supporting faster insights and improved governance. The depth of her engineering demonstrated strong proficiency in Airflow, SQL, and data engineering best practices.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
2
Lines of code
296
Activity Months1
Work History
November 2024
11 Commits • 2 Features
Nov 1, 20242024-11 Monthly Summary: Key capabilities delivered to drive analytics readiness and data reliability: 1) End-to-end Airflow data pipeline moving data from PostgreSQL to BigQuery via GCS CSV, with dynamic path resolution and robust schema handling. 2) DBT project initialization for analytics modeling, testing workflows, and schema governance. No major bugs fixed this month. Impact: centralized, query-ready data in BigQuery enabling faster insights and stronger governance. Skills demonstrated: Airflow, PostgreSQL, GCS, BigQuery, DBT, Python, and data engineering best practices.
11 Commits • 2 Features
Nov 1, 20242024-11 Monthly Summary: Key capabilities delivered to drive analytics readiness and data reliability: 1) End-to-end Airflow data pipeline moving data from PostgreSQL to BigQuery via GCS CSV, with dynamic path resolution and robust schema handling. 2) DBT project initialization for analytics modeling, testing workflows, and schema governance. No major bugs fixed this month. Impact: centralized, query-ready data in BigQuery enabling faster insights and stronger governance. Skills demonstrated: Airflow, PostgreSQL, GCS, BigQuery, DBT, Python, and data engineering best practices.
November 2024
Activity
Loading activity data...
Quality Metrics
Correctness87.2%
Maintainability87.2%
Architecture85.4%
Performance87.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQLYAML
Technical Skills
AirflowBigQueryData EngineeringData ModelingETLGoogle Cloud PlatformPostgreSQLPython ScriptingSQLdbt
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline