About This Architecture

Payment Service Provider (PSP) reconciliation pipeline ingesting daily merchant files from seven PSPs through RPA-driven batch collection into a multi-zone Snowflake data warehouse. Raw files flow through a Data Parser/Normalizer ETL layer, progressing from Bronze (unstructured CSV/XLSX/TXT) to Silver (semi-structured) to Gold (structured aggregated) zones, with SAP S/4 HANA ERP data integrated for complete transaction matching. Finance analysts extract reconciled data via Snowflake and S/4 HANA queries, with automated posting to SAP and Blackline-driven reconciliation workflows ensuring month-end close accuracy. Fork this diagram on Diagrams.so to customize PSP sources, add data quality checkpoints, or adapt the medallion architecture for your payment processing stack. The design demonstrates best-practice separation of concerns: ingestion isolation, transformation staging, and serving layer decoupling for scalability and auditability.

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How do you build a scalable data pipeline to reconcile payment files from multiple PSPs with SAP ERP?

This diagram shows a medallion-architecture pipeline ingesting daily merchant files from 7 PSPs via RPA, normalizing them through Bronze/Silver/Gold zones in Snowflake, and integrating SAP S/4 HANA data for reconciliation. Finance teams extract matched transactions to Blackline for automated posting and month-end close workflows.