Presentation
Leveraging any kind of data to uncover insights and enhance decision-making and optimize performance across complex environments.
Background
Designed and maintained data integration, processing workflows across enterprise data platforms, including Data Warehouses, Data Lakehouse environments, supporting structured data storage, transformation, consumption
Developed and maintained ETL/ELT pipelines using Python, PySpark, and T-SQL based hard coded stored procedures across Azure Databricks, Azure Synapse Analytics and Microsoft Fabric
Integrated structured data from SAP Business Warehouse, Excel, CSV, Lakehouse sources into analytical datasets
Designed analytical datasets and data models supporting pricing optimization, margin analysis, strategic business initiatives
Translated complex analytical results into practical recommendations, communicating with senior and non-technical stakeholders across five global region
Used SAP S/4HANA and VIM transactional and analytics data to support reporting, process analysis, exception investigation, audit
Analyzed purchase-order and non-purchase-order invoice processes, investigating discrepancies and supporting process control
Collaborated cross-functionally on financial processes, regulatory audits, SOX controls, and stakeholder requirements

