I will build reconciliation systems for fintech operations
About this Gig
Stop losing revenue to broken data pipelines and manual transaction tracking. Managing cross-border payments across fragmented networks introduces massive risks of operational leakage, misallocated capital, and broken reconciliation loops.
I am an elite Data and Operations Architect with enterprise-grade experience designing and maintaining automated settlement systems for a $6 Billion+ global payments network spanning 17 countries. I don't just build cosmetic dashboards; I architect production-ready infrastructure that safeguards your capital, eliminates manual overhead, and surfaces ironclad financial visibility.
Core Operational Solutions Provided:
- Automated Multi-Market Reconciliation: Custom backend logic to seamlessly ingest, match, and reconcile chaotic transaction streams across multiple payout partners simultaneously.
- Revenue Assurance & Leakage Audits: Algorithmic safeguards built natively into your data layer to instantly flag erroneous transactions, duplicate payouts, and systemic variances before they impact your balance sheet.
- FinTech Analytics Infrastructure: High-throughput data transformation pipelines mapping raw API web hook payloads, callbacks, and rate.
FAQ
Can you work securely with sensitive corporate financial data?
Absolutely. We will execute standard non-disclosure agreements (NDAs) prior to data transfer. Furthermore, all data structural design can be performed utilizing masked, anonymized production schemas or synthetic staging data to maintain complete compliance and security parameters.
Do you connect directly to financial APIs, web hooks, and third-party gateways?
Yes. I specialised in solution-architecting network configurations that ingest raw web hook callbacks, parse payload data models, handle custom rate-limiting rules, and clean up web hook failures into highly reliable data arrays.
What specific cloud and data warehouses do you support?
I specialise natively in advanced enterprise ecosystems including Google Cloud Platform (BigQuery), Databricks, and traditional Microsoft SQL Server suites (SSIS, SSMS, T-SQL).

