● Scaled Power BI dashboards across 300K+ financial transaction records, enabling real-time risk and compliance visibility for 8+ stakeholders and supporting Q1 financial planning decisions. ● Enabled ~30% faster ad hoc insights by leveraging BNY's Eliza AI APIs to accelerate financial workflows and support business decisions. ● Orchestrated Apache Airflow pipelines on Azure within Agile sprints, automating data ingestion and strengthening data governance.

● Performed funnel analysis on 5M+ user events using SQL (CTEs, window functions) and Python, uncovering drop-offs to inform A/B testing and regional pricing strategies, contributing to a 7% increase in booking conversion. ● Optimized Snowflake SQL queries through clustering and query tuning, reducing dashboard runtime from 20s to 7s across 130+ analytics workloads, improving dashboard responsiveness for stakeholders. ● Built Tableau dashboards to track platform KPIs and A/B testing results, improving demand forecasting accuracy by 9%. ● Designed dimensional models in Snowflake integrating platform and marketplace sources, standardizing KPI definitions across 6 business squads and improving consistency of executive insights and decision-making. ● Reduced production report inconsistencies by 30%, implementing automated data validation, quality checks, and schema tests in dbt throughout 40+ Snowflake warehouse tables. ● Improved pipeline reliability by managing 8 automated SSIS ETL workflows with error logging and traceability across business reviews. ● Led stakeholder review sessions with cross-functional teams, translating business questions into SQL insights that informed 15+ product and pricing decisions, documenting KPIs in Jira and Confluence.

● Analyzed 1.4M+ transactional and user-behavior records from MySQL and Google Analytics 4 leveraging SQL and Python, generating weekly KPI reports for 18 product and marketing stakeholders to monitor performance. ● Developed 23 Power BI dashboards with DAX and SQL to centralize business performance metrics, enabling leadership to review insights faster and reducing executive analytics delivery time by 75%. ● Integrated 9 operational sources through Python (Pandas) and REST APIs into centralized analytics tables in an Azure cloud platform, supporting 30+ BI requests with 99%+ accuracy. ● Identified high-risk customer segments through predictive churn modeling in Python (Pandas, scikit-learn) on Snowflake, driving a 12% improvement in campaign targeting effectiveness. ● Audited 220K+ records with Alteryx workflows, improving accuracy and ensuring compliance with governance and SDLC standards