Christine R

• Designed and implemented ETL pipelines using Python, SQL, and Azure Data Factory to process 10TB+ website traffic and customer data, reducing pipeline execution time by 40% and ensuring seamless integration for analytics teams. • Built a scalable data warehouse architecture on SQL Server to store and manage millions of rows of sales and traffic data, optimizing query performance by 50% and improving the efficiency of Tableau dashboards for decision-makers. • Streamlined data workflows by automating daily batch processes using Databricks and Python scripts, providing near real-time data availability for marketing and sales teams, which increased campaign ROI by 15%. • Developed end-to-end monitoring and alerting systems for ETL pipelines using Python and Azure Monitor, achieving a 99.9% workflow success rate and reducing pipeline downtime by 80%. • Integrated multiple data sources, including APIs and cloud-based datasets, into a centralized data platform, enabling advanced analytics and powering real-time Tableau dashboards for executive insights.

• Performed unit testing and validated stored procedures using SQL Server Management Studio (SSMS) across 20+ databases with 10 million records, ensuring adherence to 30+ business rules and 100% compliance with data cleaning standards. • Performed regression testing and query profiling using SQL Server tools, optimizing stored procedures to process 1M+ records 20% faster within SLA limits. • Partnered with ETL engineers and business analysts to identify and resolve data discrepancies, achieving 98% dataset accuracy and refining ETL transformation logic for business compliance. • Logged and tracked testing defects using Azure DevOps, ensuring detailed documentation and resolution of issues, which improved defect resolution efficiency by 20%.

• Cleaned and transformed datasets with 100K+ rows using advanced SQL queries and Excel functions (e.g., VLOOKUP, PivotTables), ensuring 100% data consistency for BI reporting. • Built dashboards in Power BI and Tableau to visualize regional sales trends, increasing decision-making efficiency by 30%. • Performed data profiling and validation using SQL joins and data checks, resolving key discrepancies and boosting data quality by 25%. • Designed and optimized SSIS ETL workflows to automate data extraction and transformation, reducing processing time by 20% and improving accuracy.

• Provided 1-1 advising sessions with students to provide support and guidance regarding the transfer process and available resources on campus. • Coordinated events for UW Madison’s Wisconsin Welcome orientation program with a budget of $30,000. • Managed social media account and created video as well as graphic content for educational and promotional uses as part of a Videography team. • Analyzed the data of previous transfer students by using Excel and Python to get visualization reports