System Overview
My data warehousing and ETL expertise spans multiple enterprise implementations, from AWS-based cloud architectures to Databricks lakehouse solutions. These systems are designed to handle massive data volumes while maintaining performance, reliability, and data quality standards.
Data Architecture Solutions
I've designed and implemented enterprise-scale data architectures that support both real-time analytics and batch processing workflows, optimized for performance and scalability.
Houston Dynamo FC - AWS Data Warehouse
Enterprise-scale ETL pipelines integrating 12+ major data sources into AWS/Postgres data warehouse with optimized query performance.
Pacers Sports - Databricks Lakehouse
Modern lakehouse architecture built on Databricks, transforming multi-source data with Databricks SQL for reliable and scalable access.
ETL Pipeline Development
My ETL processes are built for reliability, scalability, and maintainability. Each pipeline includes comprehensive data validation, error handling, and performance optimization.
Data Extraction
Multi-source data ingestion from CRM systems, ticketing platforms, digital marketing tools, and external APIs with real-time and batch processing capabilities.
Data Transformation
Custom SQL transformations, data cleansing, validation, and standardization across diverse data formats and structures.
Data Loading
Optimized loading processes with incremental updates, data quality checks, and performance monitoring for enterprise-scale datasets.
Analytics Ready
Clean, validated data available for BI dashboards, reporting systems, and advanced analytics with optimized query performance.
Data Source Integration
Successfully integrated diverse data sources across multiple domains, ensuring data consistency and enabling comprehensive analytics capabilities.
Digital Marketing Platforms
- Meta Advertising - Campaign performance and lead generation data
- Google Ads - Search and display advertising metrics
- LinkedIn Ads - B2B marketing and professional engagement data
- Conversica AI - Automated outreach and lead nurturing workflows
Enterprise Systems
- Salesforce CRM - Customer relationship and sales pipeline data
- Ticketing Systems - Event attendance and purchase behavior
- E-commerce Platforms - Online sales and customer transaction data
- Social Media APIs - Fan engagement and social performance metrics
Operational Data
- Attendance Tracking - Gameday operations and fan behavior
- Survey Systems - Post-match feedback and satisfaction data
- Sponsorship Platforms - Partnership performance and KPI tracking
- Legacy Systems - Historical data preservation and integration
Data Quality & Governance
Implemented comprehensive data quality assurance processes to ensure integrity, consistency, and reliability across high-volume datasets.
Quality Assurance Framework
- Automated Validation Rules - Real-time data quality checks during ingestion
- Consistency Monitoring - Cross-system data reconciliation and anomaly detection
- Data Profiling - Continuous monitoring of data patterns and distributions
- Error Handling - Comprehensive logging and alerting for data pipeline issues
- Data Lineage - Complete traceability from source to analytics
Performance Optimizations
- Query Optimization - Custom indexing and view structures for sub-second response times
- Incremental Processing - Delta-only updates to minimize processing overhead
- Partitioning Strategies - Optimized data partitioning for improved query performance
- Caching Mechanisms - Strategic caching for frequently accessed data
- Resource Management - Dynamic scaling and resource allocation optimization
Business Impact & Analytics
The data infrastructure directly supports critical business functions, enabling data-driven decision making across multiple departments and stakeholders.
Revenue Generation
Data pipelines feeding automated lead gen workflows enabled tracking of 350+ closed deals, contributing $675K in new revenue through optimized customer acquisition processes.
Operational Efficiency
Streamlined data refresh cycles and improved system performance reduced manual data processing time by 80% while increasing data accuracy.
Strategic Analytics
Integrated data feeds power executive dashboards for ticket sales, sponsorship KPIs, fan engagement metrics, and gameday operations analytics.
Technical Implementation Details
Each implementation leverages industry best practices for data engineering, focusing on scalability, maintainability, and performance optimization.
Houston Dynamo FC Implementation
- AWS Architecture - Cloud-native data warehouse with auto-scaling capabilities
- PostgreSQL Optimization - Custom schemas, indexes, and query optimization
- Multi-source Integration - 12+ disparate systems unified into single analytics platform
- Real-time Pipelines - Near real-time data ingestion for operational dashboards
- Vendor Collaboration - Partnered with Agilitek and AWS for architecture optimization
Pacers Sports Entertainment Implementation
- Databricks Platform - Modern lakehouse architecture with Spark processing
- Legacy Migration - Seamless historical data integration preserving continuity
- Spark SQL Optimization - Custom transformations for complex multi-table operations
- Data Model Design - Dimensional modeling for analytics and reporting
- Documentation Standards - Comprehensive workflow documentation for team handoffs
Tools & Technologies
Expertise across modern data stack technologies, from cloud platforms to specialized analytics tools.