I’m Bhargav Reddy, a software engineer with 5+ years of experience building scalable backend systems, distributed data platforms, and cloud-native applications across data infrastructure and payments. I’ve worked on high-throughput streaming and ELT/ETL pipelines, microservices, and metadata governance, with a strong focus on performance, reliability, and security. At Snowflake, I designed distributed data services and event-driven streaming architectures, improving processing latency and query performance while strengthening governance and RBAC across large schema footprints. Previously at Mastercard, I delivered real-time payment authorization and fraud detection services, integrating Kafka/AWS event pipelines with machine-learning risk scoring and PCI DSS-aligned security practices to support millions of daily transactions.

Bhargav Reddy

I’m Bhargav Reddy, a software engineer with 5+ years of experience building scalable backend systems, distributed data platforms, and cloud-native applications across data infrastructure and payments. I’ve worked on high-throughput streaming and ELT/ETL pipelines, microservices, and metadata governance, with a strong focus on performance, reliability, and security. At Snowflake, I designed distributed data services and event-driven streaming architectures, improving processing latency and query performance while strengthening governance and RBAC across large schema footprints. Previously at Mastercard, I delivered real-time payment authorization and fraud detection services, integrating Kafka/AWS event pipelines with machine-learning risk scoring and PCI DSS-aligned security practices to support millions of daily transactions.

Available to hire

I’m Bhargav Reddy, a software engineer with 5+ years of experience building scalable backend systems, distributed data platforms, and cloud-native applications across data infrastructure and payments. I’ve worked on high-throughput streaming and ELT/ETL pipelines, microservices, and metadata governance, with a strong focus on performance, reliability, and security.

At Snowflake, I designed distributed data services and event-driven streaming architectures, improving processing latency and query performance while strengthening governance and RBAC across large schema footprints. Previously at Mastercard, I delivered real-time payment authorization and fraud detection services, integrating Kafka/AWS event pipelines with machine-learning risk scoring and PCI DSS-aligned security practices to support millions of daily transactions.

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Work Experience

Software Engineer at Snowflake
May 1, 2025 - Present
Designed backend services for distributed data platforms, including scalable data ingestion for Snowflake Iceberg Tables across AWS S3 and multi-cloud environments with high availability. Built Python/Snowpark and SQL-driven processing workflows for large-scale ELT, improving query performance on 10TB+ datasets. Implemented event-driven streaming with Snowpipe Streaming to process 150K+ events/second, reducing latency to under 10 seconds. Developed metadata and governance services in Horizon Catalog with RBAC, access controls, and automated data lineage across 200+ schemas. Engineered AI-enabled backend workflows for Cortex AI integrations and supported feature engineering pipelines. Improved production reliability via Kubernetes-based deployments, CI/CD automation, and collaboration with SRE/DevOps while maintaining SOC 2 compliance.
Software Engineer at Mastercard
January 1, 2020 - November 1, 2023
Architected real-time payment authorization microservices using Java and Spring Boot with REST APIs supporting 150+ merchant/acquirer integrations, sustaining 99.95% uptime under peak load. Built event-driven transaction pipelines using Kafka and AWS, processing 12M+ payment events daily and reducing fraud detection latency from 3 seconds to under 500 milliseconds via partition tuning. Integrated Python/scikit-learn fraud detection models for predictive risk scoring, reducing false positives by 28%. Strengthened security with tokenization, encryption, and OAuth 2.0 aligned with PCI DSS across REST and GraphQL endpoints, achieving zero critical findings across multiple audit cycles. Automated CI/CD with Jenkins/Docker/Kubernetes on AWS EKS and improved deployment cycle time by 45%. Optimized PostgreSQL performance and added Redis caching to improve transaction lookup speed by 38%, while enhancing observability with Datadog and Grafana.

Education

Master’s in computer science at University of Central Florida
January 1, 2024 - December 1, 2025

Qualifications

Databricks Data Engineer Associate
January 11, 2030 - September 1, 2026
Microsoft Certified: Azure AI Engineer Associate (AI-102)
January 11, 2030 - September 1, 2026

Industry Experience

Software & Internet, Financial Services

Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
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