Hi, I'm Sumanth Varma

Designed Python-based evaluation pipelines to validate billing system accuracy, processing 500K+ daily transactions and reducing error detection latency by 40%.

Developed SQL and Pandas-driven analysis workflows to surface billing anomalies and automate performance reports, enabling faster resolution across services touching 140M+ customers.

Built scalable microservices in Python to automate billing validation and data transformation workflows, improving processing throughput by 35% on high-volume transaction queues.

Engineered automated testing frameworks achieving 90%+ code coverage, reducing regression defects by 45%. Optimized ETL pipelines to cut batch job runtime by 50%.

Collaborated with distributed systems teams to resolve API performance bottlenecks, reducing p95 latency by 30% on billing service endpoints under peak traffic load.

Developed Python and SQL-based data processing pipelines for enterprise clients, automating multi-step reporting workflows and reducing manual processing time by 55%.

Built and maintained pre-release evaluation workflows to assess software component quality, increasing automated defect detection coverage by 38% and enabling earlier identification of regressions.

Implemented Pandas-based analysis modules to extract and visualize key operational metrics, surfacing actionable insights for stakeholders across 500K+ user enterprise platforms.

Engineered RESTful backend services in Python and Java, contributing to large-scale distributed systems serving 1M+ internal enterprise users across client environments.

Automated regression testing pipelines using Python scripting, reducing manual QA effort by 60% and accelerating release cycles across 3+ simultaneous client projects.

Analyzed transaction failure patterns across payment flows using Python, identifying 3 recurring root causes in merchant-side error handling adopted by the backend engineering team.

Built SQL queries and data extraction pipelines to populate backend monitoring dashboards, improving operational visibility into merchant payment metrics for on-call teams.

Contributed to backend API improvements in Python for a merchant onboarding module, helping reduce p95 response time by 25% after profiling and fixing identified bottlenecks.

Wrote unit and integration tests for payment processing modules, increasing test coverage by 35% and enabling faster identification of regressions during deployment cycles.