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Sravanti Dandu
Mid-level Cloud Engineer specializing in AWS & Azure infrastructure automation
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Backend/platform engineer (American Express) who built a Flask-based orchestration layer to automate infrastructure provisioning and integrated Azure AD/JWT RBAC security. Strong in PostgreSQL/SQLAlchemy performance optimization (70%+ query-time reduction) and scalable async/event-driven architectures, including ML inference pipelines (SageMaker/Azure ML/Hugging Face) and high-throughput job queues (Celery/Redis) with reliability patterns like DLQs and idempotency.
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Key Strengths
- Built Flask orchestration service automating infrastructure provisioning workflows
- Modular API design with Flask Blueprints for maintainability and scaling
- Implemented Azure AD SSO + JWT-based auth with RBAC for internal endpoints
- PostgreSQL/SQLAlchemy performance tuning using JSONB/UUID/Enums plus indexes/partial indexes
- Reduced query times by over 70% via model design, indexing, and SQLAlchemy Core for analytics
- Designed event-driven ML inference pipelines using SageMaker/Azure ML/Hugging Face with SQS/EventBridge/Lambda
- Reliability patterns for async processing: unique task IDs, transactional writes, retries, DLQs, idempotency, monitoring
- Multi-tenant data isolation strategies (schema/db per tenant vs shared DB with tenant IDs + RLS)
- Optimized high-throughput background processing with Celery+Redis, batching, concurrency tuning; reduced processing time by over 60%
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