Pioneered big-data SOT for Planning platform
IaaC framework governing jobs
Optimized Spark Transfer Order pipelines speedup
Feature 01
Real-time inventory spine
I architected the streaming spine — Debezium CDC → Kafka → PyFlink stateful streaming → ClickHouse — so every SKU across 1100+ dark stores reconciles in under a minute, replacing a 30-minute batch.
Feature 02
Planning SOT at petabyte scale
I built the planning source-of-truth on PySpark, Delta Lake on S3 and Airflow, unifying FMCG, SuperStore, Cafe and Milk planning into one trustworthy layer.
Feature 03
Cost & reliability wins
I tuned the Spark Transfer Order pipelines to a 4.5× speedup, cut infra spend 30–35%, and pulled MTTR from 90 minutes down to 30.
Feature 04
IaaC governance + anomaly guard
I shipped an IaaC framework on GitHub Actions + Databricks RBAC governing 200+ jobs, plus a Z-score anomaly service (Redis + MongoDB) that pre-empts ~50% of would-be incidents.
What I shipped
Pioneered big-data SOT for Planning platform across 1100+ dark stores.
Architected real-time Inventory Consolidation: Debezium → Kafka → PyFlink → ClickHouse.
Built Anomaly Detection over Databricks telemetry with Redis + MongoDB.
IaaC framework governing 200+ jobs.
Optimized Spark Transfer Order pipelines — 4.5× speedup.