Challenge
Euroclear, a global financial transaction firm, faced challenges with scalability, data
latency, and fraud detection across 12 global regions. Their legacy data warehouse
infrastructure struggled to process 50TB+ of daily transactions, leading to high
operational costs and inefficiencies in fraud detection.
Solution
- Built a cloud-native data platform using Azure Synapse Analytics & Databricks, processing 50TB+ of transactions daily across 12 global regions.
- Reduced ETL processing time by 65%, optimizing costs by $12.1M annually.
- Deployed a real-time fraud detection system, processing 70K transactions/sec with Azure Stream Analytics & Azure Functions.
- Implemented automated data quality testing with dbt & Great Expectations, ensuring 98% test coverage across 1,500+ tables.
Cloud-Native Data Platform – Built a high-performance, scalable data architecture
on Azure Synapse Analytics & Databricks.
Performance Optimization – Implemented Delta Lake, dynamic partition pruning, and
Spark optimizations, reducing ETL processing time by 65%.
Real-Time Fraud Detection – Designed a real-time fraud scoring model, processing
70K transactions/sec using Azure Stream Analytics & Azure Functions.
Automated Data Governance – Deployed a data quality framework with dbt & Great
Expectations, achieving 98% test coverage across 1,500+ tables.
Impact
- $12.1M annual savings in operational costs
- 99.99% data accuracy, ensuring regulatory compliance
- 15-minute RPO & 1-hour RTO disaster recovery solution
