Niteesha Thottempudi

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.

Experience

Education

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