I am a Java/Python backend developer with 3.5 years of experience building scalable systems in e-commerce and search platforms. I have strong expertise in SAP Hybris, Java (Spring/Spring Boot), and Python (FastAPI), and have developed microservices, data pipelines, and search-driven features using Elasticsearch, MongoDB, Redshift, Kafka, and AWS.
In commerce, I delivered features such as Creation Nudge for PLP, wishlist, and cart pages, and built a dynamic PLP Tag system to improve product discoverability and frontend flexibility. On the search side, I implemented high-impact capabilities including SuperBrand, multiple category selection, and a price slider, requiring deep work with Java services and Elasticsearch.
I enhanced a product indexer by replacing a single-threaded architecture with multithreaded consumers integrating Kafka and SQS, enabling real-time data processing, fault tolerance, and improved throughput. I also contributed to an indexer service that reduced price update latency from 20 minutes to near real time.
Additionally, I designed ETL pipelines and Airflow jobs to process large-scale datasets, generated image embeddings, and built a microservice-based image search solution using cosine similarity. I developed batch-based indexing strategies with strong validation to ensure data quality while preventing throttling.
My experience also includes building a Neo4j-based knowledge graph for similar brand recommendations with full and incremental sync pipelines, reducing inventory update latency by 70%. Overall, I focus on performance optimization, reliable data workflows, and designing production-grade backend systems.
