Results-driven Java Spring Boot Developer with 3.7+ years of experience in designing, developing, and deploying scalable web applications and microservices. Skilled in Java 8/11/17, Spring Boot, REST APIs, Hibernate, JPA, and Microservices architecture. Proficient in integrating backend systems with databases, cloud platforms, and messaging systems.
Strong background in problem-solving, system design, and performance optimization, with hands-on experience in CI/CD pipelines, containerization (Docker), and cloud deployment. Passionate about learning new technologies and delivering clean, efficient code in collaborative environments.
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Languages & Frameworks: Java, JavaScript, Spring Boot, Spring MVC, Spring Security, Hibernate/JPA, Spring Data, Microservices, React JS, Spring AI, Spring Cloud
Databases: SQL, PostgreSQL, MongoDB
Messaging & Streaming: Kafka, Redis
DevOps & Cloud: Docker, Kubernetes, GitHub Actions, AWS, Azure, GCP, Jenkins
Other Tools: Git, Maven, SonarQube, Mend, IntelliJ, Postman
Built a scalable Medicaid fraud detection pipeline for T-MSIS claims using Databricks, Spark, and Apache Iceberg with lakehouse architecture, implementing deterministic and graph-based fraud detection using FalkorDB to identify suspicious provider–claim relationships. Orchestrated metadata-driven ETL workflows across Bronze/Gold/Active layers using ExfHarmonize and Dagster, with results stored in PostgreSQL for analytics and reporting.
Built a configuration-driven data engineering platform using Spring Boot and React.js for metadata management, ETL orchestration, and low-code pipeline design with multi-tenant support via Java SPI. Integrated distributed Spark execution across Kubernetes, AWS EMR, Azure, GCP Dataproc, and on-prem clusters, along with Keycloak-based IAM for RBAC and secure access control. Enabled document processing with OCR and search using Apache Tika and supported self-service analytics via Apache Superset.
Built an enterprise IoT-based supply chain management platform using Spring Boot and React.js, secured with Keycloak, to track and manage shipment workflows. Implemented real-time data ingestion using Confluent Kafka for IoT device streams, with scalable storage in MongoDB and AWS S3, and event-driven processing via AWS Lambda for automated document generation. Deployed the system on Kubernetes for high availability and integrated cross-cloud data transfer between AWS S3 and GCP GCS, delivering a production-grade solution for Dr. Reddy’s Laboratories.
June 2025 – Present
Designed and developed scalable, cloud-native data platforms using Spring Boot,
React.js, and
distributed data processing frameworks.
Built event-driven and metadata-driven architectures for large-scale data ingestion,
transformation, and analytics across healthcare and enterprise domains.
Implemented graph-based and rule-based processing systems for complex data relationship analysis
and fraud detection use cases.
Worked extensively with distributed systems and cloud platforms including Kubernetes,
AWS,
Azure, and GCP for multi-environment deployment and execution.
Integrated enterprise-grade security, governance, and observability features using
Keycloak, IAM
models, and analytics tools for secure and scalable applications.
Feb 2023 – May 2025
Developed enterprise-grade supply chain management applications using Spring
Boot and React.js,
with Keycloak-based authentication and authorization.
Designed scalable event-driven data pipelines using Confluent Kafka, AWS S3, AWS
Lambda, and
MongoDB to process and persist high-volume IoT device data with reliable
message delivery.
Built cloud-native solutions on Kubernetes, including automated document
generation workflows
and cross-cloud file integration between AWS S3 and Google Cloud
Storage (GCS) for seamless
client data exchange.
Delivered production-ready solutions for Dr. Reddy's Laboratories, contributing
to scalable,
secure, and reliable enterprise supply chain operations.