Mahesh Reddy
Pathoori

What I built: Enterprise Workforce Analytics & Cost Optimization Framework — integrating Workday (HCM), Jira (project tracking), and ServiceNow (ITSM) into a centralized Snowflake-powered predictive analytics platform. Built the proprietary "Run vs. Change" neural classification model that forecasts labor demand and automates contractor-to-FTE conversion recommendations across all business units. Serves as Lead Tableau Server Administrator implementing Row-Level Security (RLS) and Snowflake Dynamic Data Masking for compliance across 20+ business units governing sensitive financial data for millions of customers.

What I built: COR3 Public-Facing Disaster Recovery Transparency Dashboards — a federated Tableau architecture on AWS (Redshift + S3) unifying 15+ federal and territorial data sources into a single geospatial intelligence interface. Built custom HTML5/JavaScript front-end enabling real-time public monitoring of $20B+ in federal disaster relief funds across 10,000+ recovery projects. Automated ETL pipelines with compliance triggers replaced 72-hour manual reporting cycles with sub-hourly refreshes, serving 500+ federal, territorial, and municipal stakeholders including OIG and congressional oversight.

What I built: Treasury Risk Management & Automation Dashboard Platform — re-engineered a failing Tableau infrastructure that was causing 20–30 hours of weekly analyst downtime. Automated five critical Basel III regulatory pipelines (LCR, NSFR, Capital Position, Exposure Tracking, Intraday Liquidity, CCAR) — replacing legacy Excel-based manual processes. Optimized SQL query performance and data models to achieve 500% faster response times (minutes → sub-seconds). Built LSTM-based liquidity forecasting engine providing T+1 to T+5 breach predictions, enabling proactive regulatory buffer management before audits or Fed review.

What I built: SPOT (Security Product Order Tracking) System — an end-to-end BI platform built on Dimensional Data Modeling (Star/Snowflake schema) with automated invoice reconciliation and real-time anomaly detection. Led BI platform evaluation and Proof of Concept implementations, selecting optimal technology aligned with enterprise architecture and scalability. Architected Tableau Server governance with advanced RLS, recovering $3M annually through automated billing discrepancy detection and enabling $5M+ in additional annual savings through optimized security product ordering processes.

What I built: Network Health Intelligence Platform — as the sole BI architect, developed engineering dashboards integrating network telemetry with Jira ticketing via custom scripts for fully automated engineering workflows. Built the "High Usage Report" analytical system — a predictive failure detection tool identifying at-risk nodes before outage occurs, triggering proactive field dispatch. Implemented Tableau Server security governance and trained 50+ engineering employees on analytics-driven operations methodology.

What I built: Sales & Supply Chain Intelligence Platform — integrated distributor POS and ERP data into centralized predictive forecasting models addressing seasonal demand variability across franchise bottlers. Built Tableau-powered dashboards monitoring production efficiency and inventory turnover across international bottling operations. During this engagement, prototyped the first version of the RAG-BI (Retrieval-Augmented Generation + BI) concept — connecting an LLM natural-language query interface directly to the enterprise BI pipeline, enabling supply chain managers to ask plain-English questions of live data without SQL. This concept was later formalized, peer-reviewed, and published as the world's first RAG+BI architecture (JISEM Scopus Q4, 2025). Scalable BI templates developed here were subsequently adopted by multiple franchise bottlers across the United States.