Backend Engineer · Java · Spring Boot · Distributed Systems · Microservices

I'm a backend-focused Software Engineer with 2.5+ years building fault-tolerant distributed systems, identity/security infrastructure, and microservices at scale. I work primarily in Java, Spring Boot, and Kafka, and I like the hard backend problems — crash-safe recovery, cross-database processing, concurrency, and auth done properly.

At Maya Data Privacy I wear three hats at once — individual contributor, Scrum Master, and tester — across a ~20-person cross-functional team. I care about clean, production-ready code that holds up under real scale, and I built and open-sourced Helix, a self-hosted AI PR-review tool, on my own time.

• Languages: Java, Python, SQL, JavaScript, TypeScript
• Frameworks & Libraries: Spring Boot, Spring Security, Spring Data JPA, Hibernate, Kafka, Flyway, JUnit, Mockito
• Databases: PostgreSQL, Oracle, SAP HANA, Redis
• Cloud & DevOps: Docker, GCP, AWS, Git, CI/CD
• Observability: Prometheus, Grafana, Spring Actuator
• Testing & Docs: JUnit, Mockito, Testcontainers, Postman
• Security: JWT, RBAC, MFA, OAuth2, account security

Designing and building enterprise-grade backend systems for large-scale, privacy-focused data workflows.

• Own end-to-end feature delivery as an IC while serving as Scrum Master and tester across a ~20-person team spanning 5 functions (UI, AI, Backend, Product, Testing).
• Built a production IAM service from scratch as sole engineer — auth flows, JWT, RBAC, MFA, OAuth2, account security — now securing access for 500+ users across B2B tenants deployed on-premises.
• Designed a fault-tolerant state-management feature for long-running bulk operations across PostgreSQL, Oracle, and SAP HANA, using a crash-safe journaling pattern for automatic mid-process recovery; cut bulk insert time ~50% by disabling triggers during writes.
• Delivered across two Spring Boot microservices (Kafka/Redis) with tenant-configurable REST settings, cross-database SQL handling, and concurrency-safe resource management in a Spring Batch pipeline — validated with unit and Testcontainers tests.
• Cut a 48–60 hr workflow pipeline to ~2–3 hrs by parallelising table processing 25-at-a-time across 100k-table datasets and pushing filtering down to the database layer.
• Integrated my own open-sourced tool Helix for automated PR review, cutting review time ~50%.
• Contributed to the AWS → GCP migration, containerising services with Docker and managing secrets/connectivity across environments.

• Built a Python data-classification utility that samples field values and applies configurable detection logic to identify sensitive data types at scale.
• Implemented group-based access control to enforce data-consistency boundaries across multi-tenant workflows, hardening the authorisation model ahead of production rollout.

An open-source AI pull-request reviewer, shipped as a public Docker image so any team can pull it, deploy on their own infrastructure, and connect their GitHub org — zero vendor lock-in, no per-seat licensing. Built on weekends, then deployed and integrated into my own org's workflow, where it cut PR review time ~50%.

Java · Spring Boot · Docker · REST API · Webhooks · Ollama · LLM · GCP · Nginx

B.Tech in Computer Science — Techno India University, Kolkata GPA: 8.64 / 10 · Aug 2019 – July 2023

• Took a data-processing pipeline from 48–60 hours down to ~2–3 hours through concurrency and database-level filtering.
• Sole owner of a from-scratch IAM service securing 500+ B2B users on-premises.
• Built and open-sourced Helix, an AI PR-review tool teams can self-host — now used in production internally.

• Email: vishy.devv@gmail.com
• LinkedIn: linkedin.com/in/vishydev
• GitHub: github.com/vishy-singh
• Website: vishwajeet.me

⭐️ Always open to collaboration and interesting backend problems. Feel free to explore my repositories and reach out.