Parker Barton Email & Phone Number

- Integrated data from diverse sources using custom Python scripts, enhancing dataaccuracy and accessibility.- Developed efficient data models with DataBricks Snowflake, and DBT, solving complexbusiness issues.- Collaborated with business teams to upgrade outdated visualizations to centralizeddashboards in DOMO and Power-BI, improving decision-making efficiency.- Tracked and reported defects using JIRA and visualized reported issues in DOMO.Led the design and development of test cases in DBT for data products in a datawarehouse/lake environment, ensuring data accuracy and integrity.- Performed manual testing using SQL and Python to extract and validate data, meetingindustry standards.

- Lead cloud data migration from SQL Server to Snowflake, rewriting SQL procedureswith Python and SQL DataBricks Notebooks for better performance.- Developed and optimized complex SQL queries to analyze customer churn and identifyinfluencing factors. Used Python for statistical modeling and created visualizations tocommunicate insights, driving data-informed decision-making

- Revamped the Citrix system for capturing, identifying, and quantifying technicalsupport deflections, resulting in millions in savings. Utilized SQL, SSMS, and GoogleBigQuery for data analysis and optimization.- Designed predictive dashboards with machine learning for customer growth targets- Initiated a proactive DB error alert system, mitigating user impact

Tampa, Florida, United States

• Oversaw daily administrative operations, including club organization, outlining meeting agendas and dividing responsibilities for lower level executives• Merged NBA play-by-play and movement data that included over two million rows of data, to visualize how player spacing and much more can dictate the outcomes of plays

Fort Lauderdale, Florida, United States

• Utilized Natural Language Processing (NLP) python script to group over 300k support cases with similar to identical issues, enabling a granular view of the trending issues growing for each product.• Formulated a custom weighted calculation that displays the urgency of the support case groups, which streamlined and simplified the way stakeholders narrow down the most important cases to better reallocate their resources.• Restructured the Support database by performing multiple iterations of ETL that consolidated numerous data sources into a convenient centralized mapping.