Full Stack Platform Engineer

Job Title: Full Stack Platform Engineer (Data Ecosystem) Role Objective You will be the lead full-stack developer responsible for building our internal Data Platform Portal and the underlying integration layers. Your goal is to abstract the complexity of our data infrastructure (GCP, BigQuery, dbt, Airflow/Composer) behind a clean, component-based UI and robust APIs, enabling self-service provisioning and seamless platform workflows for technical users. Core Responsibilities 1. Frontend & UI/UX Development Component-Based UI: Architect and build a modular, reusable component library for our internal developer portal and admin consoles. UX for Technical Users: Design intuitive interfaces tailored for data professionals, focusing on clarity, speed, and reducing friction in complex workflows. Platform Workflows: Build front-end experiences for self-service infrastructure provisioning, code templates, and dynamic documentation sites. Instrumentation & Analytics: Embed telemetry within the UI to track user adoption, feature usage, and identify workflow bottlenecks. 2. Backend & Integration Engineering API Development: Design and develop highly scalable backend services and REST/gRPC APIs to power the frontend portal. Platform Connectors: Build the integration layers that enable secure, reliable communication between disparate platform components, specifically Cloud Composer (Airflow), Dataplex, BigQuery, and dbt . Auth & Security: Implement strict authentication and authorization flows (e.g., OAuth, OIDC, RBAC integration) across both the UI and API layers. Reliability: Ensure the high availability, scalability, and performance of all internal platform services. Technical Requirements (The Must-Haves) Experience: Minimum 5+ years of full-stack engineering , with a proven track record of building internal platforms, developer portals, or enterprise admin consoles. Frontend Mastery: Deep expertise in modern JS frameworks (React, Vue, or Angular) with a strong emphasis on component abstraction and state management. Backend Expertise: Strong backend language skills (Python, Node.js, Go, or Java) with expertise in building robust RESTful and gRPC services. Data Ecosystem Familiarity: While you don't need to be a Data Engineer, you must understand how data tools interact. Prior exposure to integrating with GCP services (BigQuery, Dataplex) , orchestration tools ( Composer/Airflow ), and transformation engines ( dbt ) is critical. System Design: Ability to design decoupled architectures where the UI interacts seamlessly with microservices and cloud-native APIs. What Success Looks Like Developer Autonomy: Reducing the time it takes for a Data Engineer to provision a new pipeline workspace from days to minutes via your self-service UI. Component Reusability: Establishing a core library of UI abstractions that allows the platform team to spin up new internal tools rapidly. Seamless Integration: Zero-friction API communication between our orchestration layer (Composer), governance layer (Dataplex), and execution layer (BigQuery/dbt).