Experience
Data Engineer
February 2022 – Present
- Designed efficient data models and implemented data pipelines in SQL for 500+ million row tables. Optimized data retrieval and processing on large-scale datasets achieving 40x faster query execution on these big data sets.
- Built a data pipeline using POST API to unlock Apple devices. Saved $200K/year in eCycling device costs.
- Engineered Azure Data Services with Event Hub and Logic Apps to collect and store millions of IoT device data points. Enabled real-time data analysis and monitoring for proactive decision-making.
- Led courses on the Power Stack, empowering IT analyst and dev team with advanced Power BI, Power Automate, and Power Apps knowledge.
- Applied Python to streamline $10M/year billing data and automation tasks to cloud environment, reducing manual intervention and errors. Empowered rapid iterations and data-driven improvements.
Data Engineer
May 2019 – February 2022
- Programmed in SQL to develop data quality rules to internally audit business functions connected to the businesses’ enterprise resource planning system,, for issues with corrupted or missing data and solved problems.
- Led ERP system module structure analysis and data migration to decrease yearly spend by $300k.
- Implemented distributed compute solutions in SQL for large-scale data processing, designed optimized data models with advanced window functions, and developed efficient stored procedures, resulting in significant improvements in processing time.
Key Project: Worked with the Senior Information Systems Analyst to analyze and replace ERP system module structure to improve operational efficiency in the current business environment.
Information Systems Assistantship
August 2020 – June 2021
- Taught SQL concepts including relationships, tables, and cardinality to 100+ undergraduate level students.
- Created materials and activities to increase students’ understandings of database concepts.
Software Engineer Internship
May 2018 – August 2018
- Architected a web app for accounts payable invoice system. SQL to handle database management, Python for back-end logic, and CSS/HTML for creating an intuitive and user-friendly front-end.