• Designed and shipped REST APIs and backend modules processing analytics workloads across 1M+ row datasets, integrated into production CI/CD pipelines with Docker-based containerized deployments. • Reduced bulk data upload processing time from 3 hours to under 20 minutes by engineering reusable Python services and optimizing PostgreSQL/MySQL query performance by 35–50%. • Eliminated 80% of manual reporting effort by automating recurring Excel workflows end-to-end using Python (pandas, openpyxl) and SQL, improving data accuracy across cross-functional teams. • Built 5+ real-time dashboards tracking 20+ retail KPIs; applied structured logging, error handling, and modular code standards to ensure long-term system reliability. • Contributed to Agile sprint cycles alongside engineering, QA, and data teams — driving code reviews and observability improvements that reduced mean time to detect issues.