TaylorMade Software, Inc.
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Fannie Mae Snowflake Data Lake Migration
Seamless Snowflake data lake migration and AWS optimization with Java-based APIs and validation pipelines
| Client | Fannie Mae |
|---|---|
| Challenge | Migrate Legacy Systems and Optimize Cloud Data Lake Integration |
| Result | 20% Faster Migration Pipelines and 30% Resource Savings in AWS |
| Tags | Snowflake, AWS, Big Data, Java, Python & AI, Public, Financial |
Fannie Mae engaged TaylorMade Software to lead the transition from on-prem data systems to a modern cloud-native data lake architecture built on Snowflake. The project involved optimizing AWS services and ensuring data integrity throughout the migration process.
We developed a suite of REST APIs and utility services using Java Spring Boot to integrate AWS services like DynamoDB and Kinesis. The implementation achieved 95% unit test coverage, ensuring code reliability and maintainability for enterprise use.
These services were deployed to AWS ECS Fargate, significantly reducing infrastructure overhead. This optimization yielded a 30% improvement in resource usage and improved performance across data ingestion and migration workflows.
TaylorMade Software also led the design of reconciliation and validation pipelines to support accurate and complete data migration into Snowflake. These pipelines ensured that data quality and consistency were preserved during the transition from on-premise systems to cloud infrastructure.
The successful migration established Snowflake as Fannie Mae’s centralized data lake and provided a secure, scalable foundation for future cloud-native analytics initiatives.