Accounting Data ETL Refactoring & Middle Office Integration

Project Overview

The Accounting Data ETL Refactoring project was a comprehensive enterprise initiative to modernize and optimize the accounting data processing system in response to middle office reporting system upgrades. This major effort involved refactoring 15+ ETL packages, implementing new business rules, and significantly improving processing performance. The project required coordination with overseas development resources and took over a year to complete, resulting in a more scalable and maintainable system.

Key Achievements

Refactored all accounting data ETL to conform with middle office report changes
Coordinated development with overseas resource for global team collaboration
Improved processing time from 4:00AM-5:30AM to midnight-1:30AM (2.5 hours earlier completion)
Enhanced SLA compliance with much more buffer time for issue resolution
Completed comprehensive documentation including run documents for all jobs
Integrated with existing error-reporting framework and monitoring system
Refactored 15+ ETL packages to follow consistent patterns and standards
Implemented new business rules for calculation processes and data loading
Created scalable framework for easy addition of future ETL jobs
Delivered major enterprise initiative completed over one year

Technical Architecture

Core Components

ETL Processing Pipeline
- Overnight ETL runs loading accounting, risk, and index data
- SFTP file processing and data staging
- Complex business rules application for daily and monthly holdings
- Automated data transformation and loading processes
Business Rules Engine
- Modified stored procedures for new calculation processes
- Complex business logic for data processing and validation
- Automated rule application and data transformation
- Flexible configuration for different data types and requirements
Data Staging & Processing
- SFTP file reception and staging processes
- Data validation and quality assurance
- Complex data transformation and business rule application
- Automated data loading and scheduling
Monitoring & Documentation
- Comprehensive system documentation and run documents
- Error-reporting framework integration
- Monitoring system integration for proactive issue detection
- Performance tracking and optimization

Business Impact

Performance Improvement: 2.5 hours earlier completion (4:00AM-5:30AM to midnight-1:30AM)
SLA Compliance: Enhanced reliability with significant buffer time for issue resolution
Operational Efficiency: Streamlined ETL processes with consistent patterns
Scalability: Framework designed for easy addition of future ETL jobs
Maintainability: Improved system supportability and documentation
Global Collaboration: Successful coordination with overseas development resources

Implementation Results

Before Refactoring

ETL process running 4:00AM-5:30AM with tight SLA constraints
Limited buffer time for issue resolution and troubleshooting
Inconsistent ETL patterns across 15+ packages
Limited documentation and monitoring capabilities
Manual processes for error handling and issue resolution

After Refactoring

ETL process running midnight-1:30AM with significant buffer time
Enhanced SLA compliance with room for issue resolution
Consistent ETL patterns across all packages
Comprehensive documentation and monitoring capabilities
Automated error handling and proactive issue detection

Technology Stack

ETL: SSIS packages for data processing and transformation
SQL Server: Database platform and stored procedure development
SFTP: File transfer and data staging processes
Business Rules: Complex calculation and data processing logic
Documentation: Comprehensive system and run documentation

Key Features

ETL Processing

Overnight ETL runs for accounting, risk, and index data
SFTP file processing and automated data staging
Complex business rules application for data transformation
Automated scheduling and data loading processes

Business Rules Engine

Modified stored procedures for new calculation processes
Complex business logic for data processing and validation
Flexible configuration for different data types and requirements
Automated rule application and data transformation

System Integration

Error-reporting framework integration for proactive monitoring
Monitoring system integration for performance tracking
Comprehensive documentation including run documents
Scalable framework for future ETL job additions

Data Processing

Daily and monthly holdings creation and processing
Data validation and quality assurance processes
Complex data transformation and business rule application
Automated data loading and scheduling

Future Enhancements

Cloud-based ETL migration for improved scalability and performance
Real-time data processing capabilities for faster data availability
Advanced monitoring and alerting for proactive issue detection
Machine learning integration for predictive data quality analysis
API integration for modern data exchange and processing