Dallas, Texas, United States
Who I Am Product analytics engineer/architect focusing on stored procedure/ETL pipeline creation and maintenance of the target data models used for analytics and visualizations. I understand the meaning and intent of the data. • Scalability of systems • Customer / Business requirements gathering • Source system data analysis – SQL • Data lineage / Quality • Workflow design and creation. • Analytical target model design What I Am Looking For • Product Analytics Engineer / Architect • Company that sees value in valid and accurate analytics. • Being allowed to build and populate data stores that underlie visualizations. Industries • Healthcare Experience 10+ Years Data Engineering - SQL/ETL 10+ Years Data Architect – Pipeline/Database SQL Data Technologies • DBMS: SQL Server, Oracle, Teradata • Visualization: MicroStrategy, Power BI, Tableau • ETL/ELT: SSIS, Pentaho Data Integration (Kettle) • CRM: Microsoft Dynamics 365 AI Augmentation Technologies • Player Zero • Cursor
Product Data Engineer / Architect – Data Confidence Product Goal: • Create new product line – Data Confidence / Quality. • Fit the product within the pre-existing processes and tools. Steps: • Sold the executive team on the vision which allowed me to execute the design. • Designed and implemented the analytics data model (Facts/Dimensions). • Implemented several thousand test cases. • Coded a simple linear regression algorithm in SQL stored procedure. • Communicated the nuance in the in the data produced by the Confidence product to the team building the UI components Result: • Automated process that proactively indicates whether the statistical shape of incoming data is significantly different from previous. Data Engineer – Quality Measures Goal: • Assist with deployment of quality measures for year 2026. Steps: • Compared text differences between measure year 2025 and measure year 2026 specifications – HEDIS / ACO Reach. • Determined if differences, other than value set codes, require changes in SQL Server stored procedures for the new measure year.
Data Engineer – Master Data Management Goal: • Execute on the master data management plan to create a master patient index. Steps: • Extracted list of patients and their distinct identifiable information from multiple sources. • Designated duplicate patient information from each output data set. • Merged each individual data set into one complete compilation. Result: • Compiled a distinct list of patients for ingestion into the master patient index.
Product Analytics Engineer – Pricing Project Goal: • Automate the year-end product pricing modification process. Steps: • Generated data model to hold the product pricing adjustment data. • Designed and implemented the stored procedures used to ingest and join the price increase amount to the entire customer and product catalog. • Created the Microstrategy data model – facts and attributes. • Produced end-result reporting/analytics. • Automated the error rate reporting. Result: • Allowed tracking of exact revenue dollar amount that was a direct result of the product pricing adjustment. Product Data Engineer – Sales Operations Goal: • Strategic/Key account reporting automation. • Marketo, CRM (MS Dynamics 365), and Revenue automation and integration. • Creation of Sales center contribution analytics. Steps: • Created detailed sales performance analysis for sales initiatives and strategies. • Supported reporting of acquired customers to determine which customers were lost in the process. • Coached a junior ETL developer on methods to build workflow for Marketo bulk REST api data acquisition. • Developed the workflow to extract daily the Marketo data from the bulk REST api. • Built data structures to ensure that all sales channels could be analyzed via MicroStrategy. • Enabled direct drill through from MicroStrategy dashboards directly to CRM – MS Dynamics. • Designed and built the trailing 12 months and following 12 months revenue comparison process. Result: • Sales dashboards are now updated and calculated daily instead of monthly or even quarterly. • Ensured growth for existing accounts by changing the way baseline is calculated for commission payout.