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Sayali Patil
Mid-level Python Full-Stack Developer specializing in Healthcare and FinTech
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About
Backend engineer with hands-on experience building a fraud-transaction monitoring system in Python/Flask, architected as Dockerized microservices and integrated with Kafka for high-volume streaming. Demonstrates strong performance and reliability chops across PostgreSQL/SQLAlchemy tuning (EXPLAIN ANALYZE, N+1 fixes, bulk ops), multi-tenant data isolation, and scaling via background workers + Redis caching, plus real-time ML inference deployment using TensorFlow on AWS.
Experience
Education
Key Strengths
- Built high-throughput fraud-monitoring backend with Flask REST APIs and Kafka streaming
- Designed lightweight microservices and containerized deployments with Docker
- Strong data integrity and reliability practices in Kafka (IDs/checksums, at-least-once delivery, offset management)
- Database performance tuning in PostgreSQL/SQLAlchemy (indexes, bulk ops, EXPLAIN ANALYZE, selectinload to fix N+1)
- Productionizing ML inference via Flask/FastAPI with TensorFlow on AWS (Lambda/EC2)
- Improved peak-load performance using background workers and Redis caching
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