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Navya P
Mid-Level Python Full-Stack Developer specializing in scalable microservices and cloud platforms
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About
Backend engineer who built Flask-based microservices for a high-throughput risk engine, using Kafka for streaming decoupling and Redis for low-latency caching, with PostgreSQL + Cassandra for mixed relational and time-series needs. Has hands-on experience productionizing ML inference (Azure OpenAI/TensorFlow) behind REST APIs with async queues, batching, and caching, plus multi-tenant isolation via schema separation and RBAC with per-tenant rate limiting.
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Key Strengths
- Designed Flask microservices for high-volume risk engine transactions using Kafka + Redis
- Scalability via horizontal service scaling and Kafka partitioning across consumers
- PostgreSQL performance tuning with indexing/normalized schemas; reduced query latency from seconds to milliseconds using composite indexes + pagination
- Integrated ML inference into backend via REST APIs with async processing, batching, and caching to reduce latency under load
- Multi-tenant data isolation using separate schemas and RBAC; stabilized noisy-neighbor issues with per-tenant rate limiting
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