Java Full Stack Developer

Responsibilities

• Backend & Platform Engineering
• Architect and develop highly scalable backend services using Java and Node.js.
• Design and optimize microservices deployed on Kubernetes, with strong emphasis on reliability, observability, and containernative best practices.
• Build APIs, data services, and orchestration layers supporting analytics pipelines and interactive workloads.
• Implement secure, multitenant service capabilities for analytics compute, metadata management, and platform integrations.
• Partner with SRE/DevOps on CI/CD, deployment automation, and performance tuning.
• Analytics Platform Development
• Contribute to the design of core components enabling ingestion, transformation, lineage, quality, and metadata-driven analytics.
• Build backend integrations with lakehouse, pipeline orchestration, and data catalog systems.
• Drive architectural decisions that ensure scalability for highvolume data workloads and realtime analytics features.
• MCP Frontend Engineering
• Build modern, modular UI components for the Analytics Platform using Lit.js,
• React, and the MCP design system.
• Collaborate with UX to deliver intuitive user experiences for analytics workflow creation, monitoring, troubleshooting, and governance.
• Implement clientside data visualization and interactive interfaces for pipeline insights, schema views, and usage metrics.
• Collaboration & Leadership
• Work crossfunctionally with product managers, data engineers, architects, and platform teams.
• Lead design reviews, contribute to platform architecture, and mentor junior engineers.
• Champion engineering best practices across code quality, testing, observability, and secure development.

Qualifications Required

• 5+ years of experience in backend or platform engineering roles.
• Strong proficiency in Java (preferred) and Node.js for largescale backend development.
• Handson experience with Kubernetes, containerization, microservices, and distributed systems.
• Frontend engineering experience with React, Lit.js, or other componentbased frameworks.
• Experience building analytics platforms, data infrastructure, or largescale distributed systems.
• Knowledge of REST, gRPC, streaming, caching, and eventdriven architectures.
• Excellent debugging, performance tuning, and problemsolving skills.

Preferred Skills

• Experience with lakehouse architectures, pipeline orchestration, or metadata services.
• Familiarity with MCP (Modular Component Platform) frontend patterns.
• Experience working in enterprisescale engineering organizations.
• Contributions to architectural design for complex platform systems.