Abhishek Namdev Sawant

About

Backend engineer with payments domain experience who built and operated a production-grade, event-driven payment processing platform (Java/Spring Boot on GCP, MySQL) and led reliability/performance fixes that cut peak latency by ~30%. Also shipped an applied ML capstone for the Archdiocese of Seattle, building end-to-end classification pipelines and Power BI dashboards to assess financial health and capacity utilization across 74 schools.

Experience

Education

Key Strengths

• Built production-grade payment processing backend on Java/Spring Boot microservices on GCP
• Debugged and resolved peak-hour latency/timeouts via SQL optimization, indexing, and reducing synchronous coupling (30% latency reduction)
• Designed resilient event-driven, stateful multi-step transaction workflow with idempotency, retries (exponential backoff), and manual escalation paths
• Relational data modeling for payments with audit-friendly event/state tables and integrity constraints
• Applied ML delivery end-to-end (data pipelines to Power BI dashboards) for financial health/capacity prediction across 74 schools (~69–71% accuracy)
• Strong data quality guardrails: preprocessing pipelines, schema/input validation, and safe fallbacks to prevent bad predictions

Reference Highlights

• High overall effectiveness (9/10)
• Strong performance optimization impact
• Improved microservices communication latency via redesign
• Designed reliable multi-step payment workflows across distributed services
• Strong debugging under peak-load conditions
• Log analysis to identify root causes
• Optimized critical SQL queries to improve response times
• Pragmatic use of async calls for non-critical steps
• Clean, modular, readable Python code
• Strong refactoring skills while preserving correctness
• Focuses on root causes rather than patch fixes
• Thinks through failure modes and edge cases in payment systems
• Boosted team productivity and code quality; reduced boilerplate
• Adapts well to frequent requirement changes
• Takes ownership of own and team tasks end-to-end
• Open to client feedback
• Delivered smoothly under tight deadlines and estimate constraints