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 container‑native best practices.

• Build APIs, data services, and orchestration layers supporting analytics pipelines and interactive workloads.

• Implement secure, multi‑tenant 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 high‑volume data workloads and real‑time 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 client‑side data visualization and interactive interfaces for pipeline insights, schema views, and usage metrics.

• Collaboration & Leadership

• Work cross‑functionally 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.

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 container‑native best practices.

• Build APIs, data services, and orchestration layers supporting analytics pipelines and interactive workloads.

• Implement secure, multi‑tenant 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 high‑volume data workloads and real‑time 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 client‑side data visualization and interactive interfaces for pipeline insights, schema views, and usage metrics.

• Collaboration & Leadership

• Work cross‑functionally 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.