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Niteesha Thottempudi
Mid-level Software Engineer specializing in cloud-native microservices and data platforms
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About
Backend engineer with experience at Comcast and in healthcare/pharmacy automation (PrimeRx), building Python/Flask services that orchestrate large-scale batch workflows (Airflow) and high-throughput event processing (Kafka). Demonstrated measurable performance wins (cut provisioning latency to ~150–200ms) and strong multi-tenant isolation strategies (Postgres RLS, partitioning), plus practical integration of ML model outputs into production systems with validation and fallback controls.
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Key Strengths
- Designed modular Flask backend with clear routing/service/data-access boundaries
- Built batch-oriented automation using Airflow DAGs with retries, SLAs, and monitoring
- Containerized services and managed dependency/version consistency across Flask and Airflow
- Improved ORM performance by eliminating N+1 queries via explicit joins and indexing
- Reduced device-activation latency from ~1–2s to ~150–200ms (Comcast) through query/model optimization and caching
- Integrated ML inference into backend systems using REST/gRPC and Kafka telemetry streams
- Implemented schema validation, normalization, fallbacks, and confidence thresholds to make ML outputs safe/actionable
- Designed multi-tenant data isolation using validated tenant IDs and Postgres RLS
- Mitigated noisy-neighbor multi-tenant performance issues with tenant-first indexes and partitioning high-volume tenants
- Optimized high-throughput background processing with Redis caching, batched Kafka consumption, and parallel idempotent workers
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2 publications
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