Eagle Mountain, Utah, United States
My mission is to make data easier to understand and reusable across an enterprise.
I have an exciting new opportunity at Byte, a data driven and data focused company. My role is to help design and establish a new data warehouse. The company experienced some quick startup growth and are now looking to have an established data model that will work across the enterprise.
- Full ownership of high priority BI projects from start to finish, including: working directly with customer to gather requirements, dimensional Modeling, ETL, semantic layer, and reporting in Tableau or Business Objects. - Orchestrate SQL scripts to transform customer requirements into business logic using DBT (Data Build Tool) in Amazon Redshift. - Train and mentor new hires in ETL, dimensional modeling, and Tableau. - Build SQL scripts to answer ad hoc customer business requests and troubleshoot report problems - Design and create Tableau reports for department heads - Automate data quality checks and alerts on incoming warehouse data (duplicate keys, dropped fields, etc.) - Monitor Tableau server permissions and performance, stress test with Tabjolt to simulate extreme use - Create PL/SQL automated solutions to backup team’s most important conformed dimensions
• Extract Qualtrics data utilizing SAP Data Services to transform data (used pivots, validation functions, table comparisons, key generation, etc.), then load data into SQL Server fact tables and dimensions • Create customer reports using Business Objects Web Intelligence • Verify and fix reports by querying SQL Server data warehouse, modifying ETL, and editing Business Objects Universe (i.e. fix incorrect mappings causing missing report elements, primary key duplicates, update Universe contexts and validate joins) • Convert PL/SQL views to TSQL • Analyze business needs of customer and created appropriate data models using Toad Data Modeler
• Created and managed USU MMIS Facebook, Instagram, and Pinterest pages • Tripled annual number of applications received to USU MMIS program via Facebook advertising • Utilized Google Analytics and Hootsuite to analyze data trends and manage advertising campaigns
• Imported Google Finance stock data from 15 companies into SQL Server • Queried data to return statistics such as average stock prices by company, number of companies in each industry, and most lucrative time periods via calendar and stock data joins • Used triggers to monitor updates to stock data