Venkat Pabbisetty

Project: ICREMS(Intelligent Credit Risk Evaluation & Monitoring System)

• Developed cloud-ready microservices using Spring Boot and RESTful APIs to support real-time credit evaluation, borrower scoring, and continuous risk monitoring for high-volume financial workflows.
• Integrated external credit bureaus and financial data providers to retrieve borrower credit scores, credit history, and risk indicators, enabling real-time risk scoring and downstream fraud, underwriting, and monitoring workflows.
• Implemented secure authentication and authorization using Spring Security, OAuth2, and JWT to enable stateless service-to-service communication and enforce role-based access across sensitive credit-risk operations.
• Built a scalable persistence layer using Oracle as the system of record for transactional and regulatory data, and Cassandra for low-latency, high-throughput access to real-time borrower activity and scoring signals.
• Engineered event-driven pipelines using Apache Kafka to stream borrower activity and repayment events to downstream fraud detection and underwriting services, improving system decoupling and throughput.
• Integrated Redis caching to optimize frequently accessed borrower and session data, significantly reducing response latency for real-time APIs.
• Executed Spring Batch jobs on backend services deployed through AWS ECS, automating nightly credit reconciliation and scoring workflows, and monitored them using Jenkins, Kibana, and Grafana.
• Developed internal automation utilities using Python to validate Kafka event payloads, reconcile Oracle and Cassandra datasets, and generate daily credit-risk consistency reports.
• Built modular and responsive UI components in Angular to enable real-time portfolio dashboards, borrower alerts, and operational visibility for risk teams.
• Designed and maintained batch workflows using Spring Batch to automate nightly credit reconciliation, audit log aggregation, and downstream data preparation for analytics and reporting.
• Containerized microservices using Docker and deployed them on AWS ECS, implementing rolling deployments and autoscaling to ensure high availability and operational stability.
• Built CI/CD pipelines using Jenkins, Git, and Maven to automate builds, testing, artifact versioning, and environment-specific deployments.
• Developed backend test suites using JUnit and Mockito, and implemented UI/API automation using Cucumber to ensure end-to-end validation and regression-free releases.
• Documented REST APIs using Swagger UI and OpenAPI specifications, improving service discoverability, testing, and cross-team integration.
• Implemented centralized logging and monitoring using the ELK Stack, Prometheus, and Grafana to track service health, event throughput, and error trends, enabling proactive incident management.
• Collaborated with product owners, QA, and DevOps teams in an Agile/Scrum environment to deliver secure, scalable credit-risk features on schedule.

Project: Digital Prior Authorization Platform (DPAP)

• Developed scalable healthcare microservices using Java, Spring Boot, and GraphQL APIs to automate prior authorization intake, request validation, and real-time decision support for pharmacies and payer systems.
• Built dynamic and responsive UI components using React.js, integrating backend data via Apollo Client to provide pharmacists with immediate visibility into authorization statuses and required clinical documentation.
• Integrated with external provider and payer systems using FHIR APIs and legacy SOAP services to exchange EHR data, eligibility responses, and patient-level clinical information.
• Implemented authorization-rule verification scripts in Python, validating clinical datasets exchanged through FHIR and SOAP integrations.
• Applied clinical policy rules using Drools to automate validations such as duplicate detection, dosage thresholds, and formulary compliance, significantly reducing manual review load.
• Designed routing, enrichment, and transformation workflows using Apache Camel, connecting intake services to clearinghouses, auditing modules, and internal validation components.
• Implemented asynchronous communication between microservices using RabbitMQ, improving system throughput and responsiveness during peak authorization cycles.
• Built custom API-testing helpers using Python and Postman-style scripts to validate GraphQL responses across payer systems.
• Secured APIs behind GCP IAM and Identity-Aware Proxy (IAP), ensuring HIPAA-aligned access control, encrypted transmission, and restricted service-to-service interactions.
• Built test suites using TestNG, Mockito, and REST Assured, validating API contracts, message flows, and rule-engine behavior.
• Deployed containerized microservices using Docker to GCP Compute Engine and Cloud Run.
• Monitored queue depth, latency, and failure patterns using Prometheus, Grafana, and Stackdriver, enabling proactive incident management.
• Worked with Oracle for structured clinical data and MongoDB for unstructured payloads and documents from provider systems, ensuring reliable storage across distributed services.
• Ensured HIPAA compliance through audit logging, RBAC enforcement, data masking, encryption, and row-level security applied via BigQuery policies.
• Built proof-of-concept streaming pipelines using Pub/Sub and Dataflow for near real-time authorization ingestion, alerting, and analytics.
• Implemented Cucumber BDD tests to validate React-based authorization screens and clinical information workflows.
• Documented REST and GraphQL endpoints using Swagger UI generated from OpenAPI specifications, improving developer onboarding and system traceability.
• Automated cross-browser tests using Selenium WebDriver, ensuring consistent behavior across patient request views and payer response pages.
• Delivered high-availability healthcare capabilities by collaborating with QA, DevOps, and product teams under Agile Scrum methodology.

Project: Smart Promotions Engine

• Built and maintained promotion-calculation microservices using Java, Spring Boot, Spring MVC, and RESTful APIs, supporting dynamic discount evaluations across high-traffic e-commerce storefronts.
• Developed large-scale scheduled batch workflows using Spring Batch to process promotion imports, rule synchronization, expiration handling, and bulk data transformations.
• Integrated Apache Kafka to enable asynchronous communication across checkout, inventory, and pricing services, ensuring scalable and decoupled processing during flash-sale events.
• Created Python scripts to profile large MySQL promotion datasets and validate batch-workflow outputs generated by Spring Batch jobs.
• Applied rule validations using Hibernate Validator and ensured consistency across promotion updates using Transactional for multi-step write operations.
• Wrote extensive backend test suites using JUnit and Mockito, improving reliability during high-volume sale periods and preventing regression issues.
• Used Python automation to quickly reproduce promotion-engine edge cases and assist backend debugging during flash-sale load testing.
• Built CI/CD automation pipelines using Jenkins, Git, and Maven, streamlining builds, testing, and deployment across staging and production environments.
• Maintained audit logs and activity trails for promotion changes, enabling traceability during debugging and financial reconciliation.
• Built and optimized backend builds using Gradle, improving build speed and simplifying dependency management across promotion-engine microservices.
• Collaborated in Agile sprints to deliver pricing and promotion features that supported millions of daily transactions.