Cloud-Based Data Platform & ETLModernization for Payer Systems
Enabling cloud modernization, scalable data infrastructure, and standardized analytics for a leading healthcare organization.
Client Overview
A leading healthcare organization managing multiple payer projects required a scalable, high performance data platform to support analytics, reporting, and data standardization across business units. With growing data complexity and increasing demand for real-time insights, the organization needed a modern cloud-native architecture to replace its legacy infrastructure.
Business Challenges
Our Solution
We delivered a comprehensive cloud-native data platform, combining best-in-class tools and modern engineering practices to transform the client's data infrastructure from the ground up.
Key Implementation Details
- Designed and developed scalable ETL pipelines using DBT for efficient data transformation
- Built a centralized meta package to manage dependencies and standardize transformations across projects
- Migrated the entire data platform from Azure to AWS and Snowflake for improved performance
- Integrated Amazon S3 for scalable storage and Dagster for pipeline orchestration
- Developed robust data pipelines using Python for complex data processing requirements
- Established a Single Source of Truth (SSOT) through standardized data models
- Integrated processed data with Domo for real-time reporting and analytics dashboards
- Improved modularity, scalability, and maintainability of the overall architecture
Capabilities Delivered
Scalable ETL with DBT
Purpose-built transformation pipelines leveraging DBT for modular, testable, and version-controlled data workflows.
Centralized Meta Package
A unified dependency management layer standardizing transformations and enabling rapid onboarding of new payer projects.
Azure to AWS Migration
Seamless cloud migration to AWS and Snowflake, unlocking elastic scalability and high-performance query processing.
S3 Storage & Dagster Orchestration
Amazon S3 for durable, cost-efficient storage paired with Dagster for observable, reliable pipeline orchestration.
Python Data Pipelines
Custom Python pipelines handling complex ingestion, validation, and transformation logic across data sources.
Single Source of Truth
Standardized data models eliminating inconsistencies and providing a reliable foundation for all downstream analytics.
Domo Reporting Integration
Real-time analytics dashboards powered by Domo, enabling stakeholders to make data-driven decisions faster.
Modular Architecture
Reusable, composable components ensuring long-term maintainability and accelerated delivery of future projects.
Business Impact
Reduction in development time for new payer projects
Improved scalability with AWS & Snowflake architecture
Enhanced data consistency & reduced redundancy
Faster data processing & delivery for analytics
- 40–50% reduction in development time for new payer projects
- Improved scalability and performance with AWS and Snowflake architecture
- Enhanced data consistency and reduced redundancy across payer datasets
- Faster data processing and delivery for analytics and reporting
- Increased efficiency through reusable and modular ETL frameworks
Technology Stack
Value Delivered
Through a strategic combination of cloud migration, data standardization, and modern ETL frameworks, we transformed the client's data infrastructure into a scalable, efficient, and future-ready platform. The new architecture significantly reduced development timelines, improved data quality, and empowered business teams with real-time analytics capabilities.
This engagement exemplifies how thoughtful cloud transformation and engineering excellence can drive measurable business outcomes from reduced costs and faster delivery to scalable, standardized data operations.
Want results like this for your business?
Partner with GWC to accelerate your digital transformation and drive impact.
Schedule a Strategy Call
Download Case Study