Data-driven professional with nearly 5 years of experience with big data and optimizing ETL pipelines, automating data solutions, and driving over $200 MM in savings through actionable insights and cross-functional collaboration.
Optimized ETL Pipelines : Researched, analyzed, and optimized existing ETL pipelines, reducing inefficiencies by ~90% and improving data accuracy, accessibility, and decision-making processes.
Developed MAA Data Pipeline : Designed and implemented a data pipeline framework automating data collection and integration, addressing a ~$120MM multi-account abuse problem and providing high-level reporting up to VP level.
Led Infrastructure Transition : Spearheaded the transition from legacy data infrastructure, deprecating outdated systems and saving ~104 hours of resources annually by eliminating redundancies and reducing maintenance overhead.
Built and Maintained QuickSight Dashboards : Developed and maintained dashboards for product and operations, workforce optimization, forecasting, and SLA improvements, driving operational efficiency and supporting strategic initiatives across multiple programs.
Automated Weekly Business Review (WBR) Metrics : Developed ETL workflows to automate the publication of key WBR metrics, streamlining operational reviews and ensuring timely, accurate data reporting.
Created Compromised Accounts Data Pipeline : Built and implemented a pipeline to track compromised accounts, helping mitigate a ~$75MM problem and providing actionable insights through automated reporting.
Strategic Data Analysis and Technical Collaboration: Developed data-driven strategy papers to influence key stakeholders, performed in-depth business analysis, and contributed to technical specifications, ensuring alignment between business goals and technical implementation.
Data-Driven Insights for Risk Management : Developed advanced queries and extraction techniques to identify bad actor patterns, leading to significant savings in disbursements and enhanced risk management.
Reusable Query Development : Designed reusable queries for detecting bad actor MOs, contributing to a combined ~$37.85MM savings by preventing disbursements to fraudulent entities.
Cross-Functional Data Analysis : Analyzed complex data from various sources (inventory, customer shipments, FBA ops), providing insights that identified patterns and improved bad actor risk models, leading to ~$10.1MM in savings.