Extract, clean, and massage raw qualitative and financial data sets from multiple database systems to build structured datasets for business reporting. Partner with cross-functional stakeholders to gather reporting requirements, identifying key data sources to deliver clear business narratives. Execute data validation, basic reconciliations, and data integrity checks to ensure high consistency across all operational BI models. Support monthly management reviews by querying relational databases and analyzing actual performance against budget trends.

Designed and maintained automated Python data pipelines to extract, cleanse, and structure large CSV and database files, improving report processing efficiency by 25%. Query, maintain, and optimize SQL database objects and queries to support cost structure analyses, delivering actionable insights that boosted A/B item product margins by ~10%. Built intuitive BI monitoring reports and dashboards for business unit leaders, translating raw financial/supply chain numbers into strategic executive stories. Documented operational environment metrics and BI workflows, conducting technical training sessions for end-users to enhance self-service analytics adoption. Developed structured product contribution margin datasets, giving leadership detailed visibility into cost reduction and portfolio optimization opportunities.

Developed interactive performance dashboards tracking plant metrics (Gross Sales, COGP, COGS), providing real-time visibility for operational leaders. Modeled relational data structures to build a strategic KPI variance tracking system, enabling prompt identification of operational deviations. Facilitated requirement-gathering sessions with production, finance, and supply chain teams to validate data sources and deploy accurate operational reports. Prepared root-cause variance documentation and assisted in maintaining standard cost data architecture.