Sounnish Nath

About Sounnish Nath

About:I’m a Backend & Distributed Systems Engineer focused on building scalable, intelligent, and resilient data platforms.Currently at Oracle Fusion Analytics Warehouse (FAW / FDI), I design cloud-native microservices and real-time analytics pipelines on OCI, OKE, Streaming, ATP, powering low-latency reporting and predictive insights for global enterprise customers.Before Oracle, at Tata Consultancy Services, I led major distributed systems and cloud modernisation initiatives, including:* Migrating 40M+ daily async tasks to Pub/Sub + Spark + Delta Lake → 68% cost reduction* Re-architecting a Golang + Kafka orchestration engine → 64% faster analytics workloads* Designing low-latency GraphQL Data APIs serving 3.5TB+/month at 300ms P95* Building enterprise search with LLMs + vector DBs achieving 88.4% retrieval accuracyI love designing systems that scale, self-heal, and stay performant under load — whether it’s streaming architecture, distributed consensus, large-scale data pipelines, or AI-assisted cloud services. Core Areas of ExpertiseGo • Python • Java • SQL • Kafka • Spark • Redis • Postgres • Oracle ATPKubernetes • Docker • Pub/Sub • BigQuery • OCI • GCP • Distributed SystemsMicroservices • System Design • Streaming • Caching • Observability • DevOps / CI-CDLLMs • Vector Databases • HuggingFace • AI-driven Automation Let’s build something impactful https://github.com/sounishnath003 https://sounishnath.netlify.appOpen to opportunities in:Software Engineering • Backend Engineering • Distributed Systems • Data Engineering • Cloud Platforms

Experience

1. Software Engineer Ii

   Oracle

   Apr 2025 — Present · Bengaluru, IN

   Developing intelligent RCA (Root Cause Analysis) automation leveraging LLM-based algorithms on the OCI AI & Data Science stack, enabling leveraging LLM-based algorithms for slow-running Fusion SCM analytics jobs (>10s), cutting triage time by 40% and improving developer productivity by 20%- Engineered predictive analytics workflows in Fusion Intelligent Applications (IApps) to capture real-time alert metrics and proactively mitigate cascading failures in supply chain production pipelines, leveraging OCI Streaming, Autonomous DB, and AI/ML services; improved system resilience and reduced downtime risk by 30%- Working on backend pipelines by introducing adaptive query caching, parallelised execution plans, and workload-aware resource allocation, resulting in 15% faster report generation across large-scale datasets- Collaborated with cross-functional teams to define and refine complex star and snowflake schemas within Oracle Fusion Data Intelligence (FDI), enabling streamlined query performance for business analysts- Partnered with Product & Data Science teams to integrate predictive workload analytics, proactively identifying bottlenecks before SLA breaches.

Education

• Ghatal Vidyasagar High School - (GVHS)

  Higher Secondary Education, Science

• Sabita Devi Education Trust, Brainware Group of Institutions 270

  Bachelor of Technology - BTech, Computer Science

  2017