KRISHNA VARMA NADIMPALLI

Backend engineer on an enterprise platform for managing network infrastructure data, working on Java REST services, a MongoDB-to-graph data integration, and related supporting systems.

Java Backend & REST Services

• Developed REST APIs in Java / Spring Boot for a microservices platform deployed on Kubernetes, serving several internal client applications.
• Worked with MongoDB as the primary datastore and added a Redis caching layer to reduce repeated reads on frequently hit endpoints.
• Implemented role-based access control through API middleware, with permission checks applied at the route level.
• Built master/sub-project relationships in the data model, including roll-up aggregation of child records to parents, supported by MongoDB indexes for reporting queries.
• Added server-side validation for domain rules — preventing circular parent/child references and invalid state changes on completion and deletion.
• Integrated Kafka for event messaging between services and S3 for document/attachment storage.

Data Integration — MongoDB to Neo4j

• Built a Python service to move data from MongoDB into a Neo4j graph database, used for relationship-based queries that were slow against the document store.
• Supported two ingestion paths: a full load for initial migration and an incremental change-data-capture (CDC) path driven by MongoDB change streams.
• Used Cypher MERGE/DELETE so repeated or replayed events produced the same graph state without duplicate nodes or relationships.
• Staged change events as files on Linux/S3 (CSV for batch, JSON/CSV for CDC) before loading into the graph.
• Added a retry worker that re-processes failed records with a configurable retry count and interval, tracks per-record status, and sends email notifications on failures.
• Modeled network assets and their connections as a graph to support multi-hop traversal and impact analysis; managed the service through GitLab CI across dev, QA, UAT, and prod.

Environment: Java, REST APIs, MongoDB, Neo4j (Cypher), Redis, Kafka, Socket.io, Amazon S3, LDAP, Kubernetes, Helm, Docker, Jenkins, GitLab, Linux.

Backend engineer building Java services for a community safety app that lets citizens report incidents and receive real-time alerts about activity near them.

• Developed REST endpoints in Java to submit, update, and query incident reports, each capturing category, location, description, and reporter details.
• Wrote the data-access layer in Java to persist incident reports and their status history to MongoDB, with location stored for proximity-based lookups.
• Implemented server-side validation in Java to ensure data integrity by verifying required fields, rejecting duplicate reports, and confirming category and severity before report submission.
• Established mapping logic between API request/response objects (DTOs) and stored entities, ensuring API contract stability amidst data model changes.
• Built a Kafka consumer in Java to process incident lifecycle events (reported, verified, assigned, resolved) and apply the corresponding status changes.
• Triggered push notifications from service-side events to alert nearby users and patrol volunteers when a relevant incident was reported.
• Wrote unit tests with JUnit and Mockito across service and data-access classes, and validated endpoints during development with Postman.
• Applied OAUTH/SSO token validation on incoming requests to secure the APIs and scope access by user role (citizen, volunteer, moderator).
• Added SLF4J logging shipped to Splunk for troubleshooting and operational visibility.
• Built with Maven and deployed through GitLab CI/CD to a Kubernetes environment, contributing through code reviews and iterative tickets.

Environment: Java, Spring (core), REST APIs, MongoDB, Kafka, JUnit, Mockito, Maven, GitLab CI/CD, OAUTH/SSO, Kubernetes, Splunk.