Java Full Stack Developer with Backend Focus
Role
Java Full Stack Developer — Backend Focus
Grade
Assistant Vice President
Location
Mumbai
Reports To
TBC
About BNP Paribas India Solutions
Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, European Union’s leading bank with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 10000 employees, to provide support and develop best-in-class solutions.
Position Purpose
Design, develop, and maintain robust, scalable Java-based backend services and middle business layer components within enterprise full-stack applications. Own backend architecture decisions, API design, data access patterns, and integration with upstream and downstream systems. Work competently across the existing frontend layer using Angular/TypeScript/React. Bring the depth of an experienced backend engineer with the breadth to contribute across the full stack. Leverage AI-assisted development tools as a standard part of day-to-day engineering practice.
Direct Responsibilities
• Design and Develop scalable full-stack solutions using Java, Spring Boot, and modern frontend frameworks (React/Angular).
• Design and optimize high-performance APIs with security, caching, and fault tolerance.
• Design and Develop robust backend services with efficient database interactions.
• Build responsive UI with seamless backend integration.
• Automate CI/CD pipelines for rapid, reliable software delivery.
• Lead cloud-native deployments with containerization, auto-scaling, and cost optimization.
• Enforce Quality-first engineering: Unit, integration, and ensure high code quality with SonarQube.
• Mentor junior developers, conduct code reviews, and drive technical excellence across the team.
• Collaborate with stakeholders to translate business needs into robust, compliant technical solutions.
Contributing Responsibilities
• Contribute to technical design discussions and architecture decisions, particularly around API design, data layer, and system integration
• Participate in code reviews and enforce clean code and quality gate standards
• Support knowledge transfer and capability building within the India Solutions team
• Collaborate with cross-functional teams (frontend, QA, infrastructure) on integration and delivery
• Improving DevSecOps maturity and SDLC practices within the team
Technical & Behavioral Competencies
- Autonomy & Ownership: Ability to work autonomously and take end-to-end ownership of backend components
- Industry Expertise: Experience in large-scale regulated enterprise environments (banking/financial services preferred)
- Collaboration & Communication: Strong collaborative and communication skills to work in a global team
Specific Qualifications
Experience Level: 8+ years
• 7+ years with Java backend development at enterprise scale
• 5+ years with Spring Boot/Spring MVC in production environments
• Demonstrated good experience across the listed Technical skills.
• Familiarity with frontend integration using Angular/TypeScript/React
• Experience with legacy system refactoring to target architecture
• Active use of AI coding assistants in daily workflow
Domain Experience
• Banking, financial services, or similarly regulated enterprise environments preferred
• Experience in GCC or offshore delivery models advantageous
• Exposure to high-volume, high-availability backend systems
Technical Skills
Required:
Skill Group
Details
Core Java & JDK 21+
1. Modern language features – records, sealed classes, pattern‑matching, text blocks, and functional APIs (streams, Optional).
2. Concurrency & Parallelism – virtual threads (Project Loom), Completable Future, Executor Service, Fork/Join, and basic lock/atomic primitives.
3. JVM & GC tuning – G1/ZGC behaviour, heap‑dump analysis, JFR profiling, and module‑system (JPMS) usage.
4. Logging / Instrumentation / Error Handling
5. Build & Unit‑test foundation – Maven/Gradle multi‑module builds, JUnit 5 + AssertJ, static code checks (SpotBugs), and basic GraalVM native‑image awareness.
Spring Ecosystem
1. Spring Boot 3.x – create micro‑service skeletons, auto‑configuration, actuator health‑checks, and simple security (JWT/OAuth2).,
2. Spring Data (JPA/R2DBC) – entity mapping, query‑hint optimisation, reactive repositories, and transaction demarcation.
3. Spring Cloud basics – service discovery (Eureka), API‑gateway pattern, externalized config (Config Server), and circuit‑breaker (Resilience4j).
4. Either Spring Batch OR Spring MVC OR Spring Integration
5. Spring Security– CSRF protection, OAuth2 resource‑server setup, basic role‑based access control, and token validation, zero trust, MTLS.
Database & Data Access Engineering
1. SQL & query optimisation – complex CTEs, window functions, indexing strategies, and execution‑plan analysis (PostgreSQL/Oracle/MySQL).
2. Database optimisation - (indexing, query plans). Understanding of partitioning
3. ORM performance – JPA/Hibernate mapping, N+1 detection, second‑level cache, batch inserts/updates, and @QueryHints.
4. NoSQL & caching – when to use MongoDB, GraphDB, Redis (session/Cache‑aside), basic data‑modeling, and TTL/eviction policies.
5. Migrations & transactions – Flyway/Liquibase versioning, multi‑DB transaction handling (JTA), and isolation‑level choices.
Design & Architecture
1. Clean / Hexagonal architecture – ports‑and‑adapters, dependency‑inversion, and keeping frameworks at the outer ring.
2. Domain‑Driven Design basics – bounded contexts, aggregates, domain events, and idempotent processing.
3. API‑first & contract – OpenAPI/Swagger spec authoring, versioning strategy, and consumer‑driven contract testing (Pact).
4. Event‑driven patterns – Kafka or RabbitMQ producers/consumers, out‑box pattern, and basic saga (choreography) implementation.
5. Security: Public Keys / Hash Concepts. Design around Access Control, Role Based security.
6. Microservices design Pattern ex: SAGA Design pattern
Concepts like -Circuit breaker, load balancer, Reverse Proxy
7. Integration Patterns, Enterprise Patterns, Application scalability (stateful & stateless), Microservices Patterns, Distributed Transactions
8. Caching Strategies (Redis, CDN)
DevOps
1. Containerisation & K8s – Docker multi‑stage builds, Helm chart basics, pod liveness/readiness probes.
2. CI/CD pipeline – Jenkins/Argo CD job that runs unit, integration, and static‑analysis steps; artefact publishing. Pipeline-as-code (Jenkinsfile/YAML)
3. Observability starter – expose Prometheus metrics, configure a basic Grafana dashboard, and ship structured logs to ELK.
4. Runtime security, secret‑management (CyberArk / Hashicorp / equivalent)
5. Canary/blue‑green release patterns
Testing & Quality Engineering
1. Test‑pyramid implementation – unit (JUnit 5/Mockito), integration (Testcontainers), contract (Pact).
2. Performance & load testing – JMeter script creation, baseline latency/SLO definition, simple analysis of results.
3. Static analysis & coverage – SonarQube quality gate, JaCoCo coverage threshold, SpotBugs rule set.
Frontend
Proficient working within existing Angular/TypeScript/NodeJS/NPM frameworks.
AI Tools
Daily use of AI DevAssistants (e.g., Claude, GitHub Copilot) to accelerate implementation across all skill areas
Understanding of MCP and Agentic concepts and able to develop and design.
Experience with Prompt Engineering, codebase context and constraints of AI assistants
Behavioral Skills
• Sets technical direction for multiple squads and aligns it with business objectives
• Cross-functional collaboration across frontend, QA, DecvSecOps and infrastructure teams
• Balances speed, quality, and regulatory constraints in a fast-moving environment and is results oriented
• Ensures that security, data‑privacy, and regulatory requirements are baked in.
• Structured communication of technical decisions to non-technical stakeholders
• Adaptability to legacy and greenfield environments delivering modern, cloud‑native solutions.
• Leverages generative AI to boost productivity and foster a culture of experimentation
Education Level: Bachelor's degree in Computer Science, Engineering, or equivalent professional experience
