Case study
Citizen Data Platform (Government)
Built scalable backend APIs and resilient background processing for a citizen data platform handling millions of records with high integrity and availability.
- Role
- Technical Lead
- Published
- Tags
- government · citizen-data · backend · hangfire · data-integrity
Citizen records
10M+
Large-scale public-sector data processing
Uptime
99.9%
Production availability target
Problem
The platform needed to process millions of citizen records reliably. Data quality, availability, and synchronization behavior mattered more than raw feature count because downstream systems depended on consistent citizen information.
Solution
I built scalable backend APIs, implemented background jobs with Hangfire, and designed a resilient data synchronization architecture. The system separated request handling from long-running processing so large workloads could be retried, monitored, and corrected without blocking user-facing operations.
Architecture decisions
- Backend APIs were designed around clear contracts and validation to protect data integrity at the system boundary.
- Hangfire handled background jobs, retries, and operational visibility for long-running processing.
- Data sync was designed to tolerate partial failure and preserve consistency across downstream systems.
Impact
- Supported reliable processing of 10M+ records.
- Maintained high data integrity and availability with 99.9% uptime.
- Reduced operational risk by making background processing and synchronization behavior visible.