⚠️ Project Status: PlanningThis project is currently in the architecture and design phase. The implementation will focus on building a high-performance financial reconciliation engine capable of processing both large batch workloads and real-time transaction streams using modern distributed system practices.
This project aims to build a financial reconciliation engine designed to compare large volumes of internal transactions against external bank statements, automatically identifying inconsistencies while ensuring data accuracy and consistency.
The objective is to build a robust Java-based reconciliation engine capable of processing multi-gigabyte files through batch workloads while simultaneously reconciling real-time transaction events without waiting for scheduled executions.
Batch processing will be implemented using Spring Batch, defining complex jobs responsible for reading, validating, transforming, and reconciling large financial datasets, including bank statements exceeding 10 GB. These jobs will be orchestrated through Kubernetes CronJobs, enabling automated daily reconciliation workflows.
For continuous reconciliation, the platform will leverage Kafka Streams to process financial events in real time. Incoming transactions such as payments, refunds, reversals, and corrections will be reconciled immediately as they are published, reducing reconciliation delays and improving financial consistency.
Raw reconciliation files will be stored in Amazon S3, while processed reconciliation results and analytical data will be persisted in Amazon Redshift, creating a scalable architecture optimized for reporting and financial analysis. The infrastructure will be provisioned using Terraform, ensuring reproducible and version-controlled cloud environments.
To provide operational visibility, the platform will include observability through Datadog, monitoring batch executions, worker health, processing throughput, Kafka consumer lag, and overall system performance.
The final solution will combine batch processing, stream processing, cloud infrastructure, and microservice design, following modern software engineering principles to simulate the architecture commonly found in banking systems, payment processors, and financial institutions handling high-volume transaction reconciliation.