Led the design of a scalable, risk-oriented payment processing layer, integrating multiple systems and significantly reducing financial risks.  Spearheaded the development of a real-time data processing platform using Kafka and Presto, managing over 1 billion transactions daily and achieving an 80% reduction in latency.  Directed innovations in data integration using MongoDB , enhancing data accessibility by 75% and maintaining high data quality.  Actively contributed to the strategy and execution of systems supporting real-time crypto trading, focusing on performance and reliability

Initiated and developed a Kafka-centric real-time data pipeline, aimed specifically at monitoring financial risks. This infrastructure enabled rapid insights into potential fraudulent activities and enhanced the overall responsiveness of the risk team.Played a pivotal role in refining ETL patterns for the backend systems. These optimizations ensured smoother and more efficient risk evaluations, especially during peak trading times, reducing system latencies and enhancing user experiences.Led the initiative in conceptualizing and deploying intricate risk data models. These models supported various use-cases and were fundamental in driving risk detection efficiency across several platforms and products.

Developed and maintained robust, large-scale data processing systems, achieving a 99.9% uptime.Collaborated with stakeholders, ensuring the provision of relevant data insights through visualizations and models, supporting informed decision-making.