Ismail Wahba

• Developed a python library for exploratory data analysis and machine learning models evaluation, reducing 25% of the development time. • Created APIs for enriching the customer data platform daily with 50M records from diverse sources using SFTP, HTTP, Facebook and Google APIs. • Lead communication with online-marketing team to optimize site search traffic for 26 domains with 45M clicks monthly. • Used AWS Sagemaker XGBoost machine learning model for predicting churn rate based on previous events.

Developed a framework to ensure Data Lineage and compliance with business rules across various Data Warehouse layers saving 25% of daily manual work. • Developed a Quality Framework for Data Profiling and eliminating Data Modeling inconsistencies which reduced process time by 95%. • Created scripts for automatically reflecting changes in the EDW Physical Model to production environment that led to 80% increase in process speed. • Lead the meta-data management initiative of the new Enterprise Data Warehouse.

• Designed, developed and tested ETL pipelines for Banking and Teleco clients from source systems to the Data Warehouse which ingested 100+ million transactions. • Developed a meta-data framework for tagging and tracking 1000+ ETL processes which acquired statistics for completeness checks and future optimization. • Coded SQL scripts to apply business rules and populate the Data warehouse reporting layer. • Developed ETL processes to meet service level agreements for data timeliness and frequency.

Developed SSIS ETL packages to gather and transform data from source systems and load it into implemented Data Warehouse. • Built Multidimensional and Tabular Model SSAS OLAP cubes for data analysis and insights discovering. • Developed Ad-hoc reports, Dashboards and Scorecards using SSRS based on the defined Business Objectives and KPIs.