Connor Shepler
Data Architect &
Have worked in a variety of positions, including key developer, solution designer, and data architect.
Strong engineering background combined with closely working with business customers to deliver actionable insights.
400+
Completed
Projects
10+
Years of
Experience
6+
Years of
Microsoft Power BI/Fabric
Experience
Results-driven Data Warehouse Architect/Engineer with proven success in the design, development, and deployment of business intelligence solutions. Passionate about utilizing technology to solve complex problems and drive data-driven decision making.
I specialize in transforming raw data into actionable insights using Microsoft technologies such as Micorosoft Fabric, Azure Synapse Analytics, and Power BI. With a decade worth of experience within the healthcare sectors, I bring a comprehensive understanding of business needs and technical implementations.
Outside of work, I enjoy exploring emerging technologies, contributing to open-source projects, and continuously expanding my technical expertise.
I'm open to discussing job opportunities, data engineering projects, or just connecting with fellow professionals. Feel free to reach out to me on LinkedIn.
Professional Networking
Connect with me on LinkedIn to view my complete work history, skills, and recommendations.
Visit my LinkedIn profileUS National Debt Clock
Interactive visualization demonstrating real-time data tracking and visualization capabilities.
Historical Debt Trend (30 Days)
Data source: U.S. Treasury Fiscal Data API - Debt to the Penny
Chart shows the total public debt outstanding in trillions of dollars
About This Visualization
This interactive data visualization demonstrates my capabilities in:
- Real-time data processing - Tracking dynamic data with live updates
- API integration - Connecting to and handling external data sources
- Responsive visualization - Creating charts that work across device sizes
- Error handling - Graceful fallbacks when data sources are unavailable
- Data transformation - Converting raw data into meaningful visualizations
Similar techniques can be applied to business metrics, performance indicators, and other real-time data tracking needs in professional applications.