Enterprise Data Migration Platform at OneTrust

Challenge

Following OneTrust's acquisition of Convercent, I was tasked with creating a mission-critical data migration platform to transfer terabytes of sensitive compliance data across different database schemas while maintaining strict data integrity and privacy requirements.

Technical Solution

I designed and implemented an enterprise-grade ETL pipeline with Django APIs handling complex schema transformations across 50+ data types. I built flexible mapping engines to accommodate customer-specific data structures and implemented parallel batch processing to optimize performance.

Python Django PostgreSQL Kubernetes Docker
Business Impact

The migration platform achieved 99.9% data accuracy with zero privacy violations, successfully migrating 20+ enterprise clients with zero data loss incidents. This accelerated time-to-value for the acquired customer base and ensured business continuity during the transition.

AI-Powered Chatbot Integration at SecurityScorecard

Challenge

At SecurityScorecard, non-technical users struggled to interact with complex security data, limiting the platform's accessibility and adoption.

Technical Solution

I built a Langchain-powered chatbot with FastAPI that provided a natural language interface to the security data. The system included context-aware query processing and maintained user session state for follow-up questions.

Python FastAPI Langchain Snowflake
Business Impact

Systems I developed contributed to a 30% increase in API usage and enabled the platform to handle 3x more vendors per customer. The chatbot specifically improved platform accessibility for business users, increasing engagement with security insights.

High-Performance API Infrastructure at Globo.com

Challenge

While at Dextra Digital, I worked with Globo.com to develop APIs that could handle extreme traffic spikes during major media events, with requirements to process 500K+ requests per hour without performance degradation.

Technical Solution

I architected a distributed API system using Flask and Django that implemented advanced caching strategies, connection pooling, and asynchronous processing for compute-intensive operations. I designed the system with horizontal scalability in mind, allowing for dynamic resource allocation during peak events.

Python Flask Django Redis Asynchronous processing
Business Impact

The API infrastructure successfully handled major Brazilian media events with zero downtime, processing over 500,000 requests per hour during peak times. The system's reliability ensured consistent user experience during high-profile broadcasts, directly contributing to Globo's digital media strategy and advertising revenue targets.

Secure Authentication for Venmo at PayPal/IKTech

Challenge

At IKTech, I worked on PayPal/Venmo's financial transaction systems, where enhancing authentication security was critical while maintaining seamless user experience across millions of daily transfers.

Technical Solution

I created Python validation decorators that prevented common attack vectors by implementing multi-layered verification checks. I developed comprehensive QA testing frameworks covering 20+ edge cases and potential security vulnerabilities. The authentication system incorporated device fingerprinting, behavioral analysis, and progressive security challenges based on risk assessment.

Python Kubernetes SSO workflows CI/CD pipelines
Business Impact

The enhanced authentication system significantly reduced fraudulent authentication attempts while maintaining the ease-of-use that Venmo users expect. The security improvements helped protect millions of dollars in daily transactions without negatively impacting the user experience or transaction completion rates.

WebSocket Stress Testing for Caixa

Challenge

At Dextra Digital, Caixa needed to validate that their new real-time banking platform could handle extreme concurrent connection loads without performance degradation or connection failures.

Technical Solution

I designed and implemented a WebSocket stress test suite capable of simulating 130K concurrent connections. The testing framework included realistic user behavior patterns, variable connection/disconnection rates, and detailed performance metrics collection to identify bottlenecks.

Python WebSocket libraries Distributed testing
Business Impact

The comprehensive stress testing identified several critical performance issues before production deployment, potentially preventing system outages that would have affected thousands of banking customers. The testing suite became a standard part of Caixa's release process, improving overall platform stability.

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