Ammar Rehman

- Develop scalable data analytics products by building robust data pipelines, implementing CDC for incremental loads and SCD Type 2 for historical tracking, ensuring accurate insights for business stakeholders. - Design and optimize backend data models with referential integrity to support analytics and reporting, improving data governance and enabling trust in data-driven decision making. - Implement JSON structures within entities to enable flexible indexing and enrichment, forming the backbone of an AI-driven search solution that improved accuracy and scalability in web applications. - Improve system performance by tuning SQL views (indexing, query rewrites), reducing query runtimes and lowering compute resource consumption and devise Cloud object storage cleanup strategies to manage costs, demonstrating entrepreneurial thinking and a customer-focused approach. - Streamline deployments with GitHub CI/CD, fostering a collaborative development culture, supporting agile delivery, and reducing operational bottlenecks. - Partner with cross-functional teams to ensure data engineering deliverables translate into tangible business outcomes.

I have been working here as a part of Business Intelligence and Data Warehouse Team. My responsibilities include, but are not limited to, the following: • Responsible for all interdepartmental business intelligence reporting requirements elicitation. • Ensured accuracy of data, and deliverables by understanding rules commercially. • Extracted revenue and conversion trends for Pre and Post Campaign analysis. • Automated Report Extraction via Shell scripting which reduced Adhoc requests by 60%. • Communicate results and business impacts of insight initiatives to stakeholders within the organization.

• Analyzing the trends in call patterns of different subscribers and based on the analysis; develop a subscriber churn prediction model. • Dealt with the problem of class imbalance using resampling methods. • Executed conventional Data mining methods like Regression analysis, Neural Networks and Decision trees. • Achieved an overall accuracy of 73%, while testing of model. • Generated BI reports and dashboards showing characteristics of potential churners.

Developed ad hoc reports using SAP Business Objects (Web Intelligence). Contributed to the development of dynamic dashboard showing ETL process execution summary using SAP Xcelsius Dashboards. Reorganize documents on SharePoint Portal.