Ready to Connect Your Systems?
Let's discuss your data integration challenges and design a solution that works for your specific environment.
Contact Me1314 South 1st Street, Unit 206 Milwaukee,WI 53204, US
1314 South 1st Street, Unit 206 Milwaukee,WI 53204, US
Let's discuss your data integration challenges and design a solution that works for your specific environment.
Contact Me
Data integration is the process of combining data from multiple disparate sources into a unified, usable format. For enterprise organizations, this typically means connecting legacy systems, modern APIs, cloud services, and databases that were never designed to work together.
The challenge isn’t just moving data—it’s transforming it correctly, handling authentication across different systems, managing errors gracefully, and ensuring data quality throughout the pipeline.
Multi-System Consolidation
Your data lives in agent management systems, accounting software, CRM platforms, and legacy databases. I build ETL pipelines that extract, transform, and consolidate this data into a single source of truth.
API Integration with Legacy Systems
Modern SaaS platforms offer REST APIs, but your core business runs on systems built decades ago. I create the bridge between these worlds, handling OAuth authentication, JSON transformation, and database updates.
Complex Data Transformations
Hierarchical commission structures, multi-level agent relationships, GL account mappings—enterprise data is complex. I design SQL Server schemas and Python transformation logic that preserve business rules while making data accessible.
Automated Data Pipelines
Manual data exports, Excel transformations, and email attachments don’t scale. I automate the entire flow with scheduled jobs, error notifications, and comprehensive logging.
Python ETL Pipelines
Custom Python scripts that handle file processing, API calls, data validation, and database loading. Built with robust error handling, state management, and retry logic.
SQL Server Integration
Stored procedures, staging tables, MERGE statements, and recursive CTEs for complex data relationships. Proper normalization, indexing, and performance optimization.
Azure Data Factory
Cloud-based orchestration for scheduled pipelines, monitoring, and scalability. Integration with Azure B2B for secure cross-organization data sharing.
REST API Integration
OAuth2 authentication flows, JSON parsing, rate limiting, and pagination handling. Experience with AgentSync, financial services APIs, and custom enterprise endpoints.
File Processing Automation
CSV, Excel, fixed-width files—I handle them all. Automated pickup from SFTP/Azure/network shares, validation, transformation, and loading with complete audit trails.
Insurance Agent Data Sync
Automated daily integration between AgentSync API and legacy Prism system. Handles 5,000+ agent records with OAuth2 authentication, JSON-to-SQL transformation, and conflict resolution.
Financial Services GL/AP Automation
Multi-source data consolidation from accounting systems, check processing, and payment platforms. Automated file pickup, validation, transformation, and loading with comprehensive error reporting.
Commission Processing Pipeline
Hierarchical agent relationships with multi-level commission splits. Complex SQL queries with recursive CTEs, automated calculation validation, and exception handling.
Eliminate Manual Work
Stop spending hours copying data between systems. Automation runs 24/7 without errors or fatigue.
Improve Data Quality
Automated validation, transformation rules, and error detection catch problems before they impact your business.
Enable Better Decisions
Consolidated data means better reporting, analytics, and business intelligence. See the complete picture across all systems.
Scale Your Operations
Manual processes break down as volume grows. Automated integration scales effortlessly.
Reduce Risk
Audit trails, error logging, and validation rules ensure compliance and traceability.
Discovery (1-2 weeks)
I analyze your source systems, data structures, business rules, and integration requirements. Document authentication methods, transformation logic, and error scenarios.
Design (1-2 weeks)
Create the integration architecture: staging databases, transformation logic, error handling, scheduling, and monitoring. Review and refine with your team.
Implementation (2-8 weeks)
Build and test the pipeline. Iterative development with regular check-ins, test data validation, and refinement based on feedback.
Deployment & Knowledge Transfer
Deploy to production with monitoring and documentation. Train your team on operation, troubleshooting, and maintenance.