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Mid-level popular fullstack role, metro location, and broad tech stack create high applicant competition.
Core full-stack skills are transferable, but data-quality, analytics and GCP specialization moderately limits cross-industry fit.
Explicit 5–8 year requirement plus many mandatory frontend, backend, cloud and IaC skills increases filter rigidity.
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Design, develop, and scale full-stack Data Quality and AI-enabled platforms with React, TypeScript, Python (FastAPI), delivering responsive web apps, APIs, and AI capabilities.
Build and enhance scalable Data Quality and Governance solutions including rule management, observability, anomaly detection, metadata monitoring, and AI-powered insights.
Develop cloud-native applications with GCP, containerization (GKE), CI/CD pipelines (Terraform preferred), and integrate Generative AI and ML models for intelligent workflows.
5-8 years professional full-stack/software engineering experience with end-to-end system ownership.
Strong frontend skills: React/Angular, TypeScript, JavaScript (ES6+), HTML5/CSS3.
Strong backend skills: Python, FastAPI or Flask, SQL (analytical queries on large datasets), REST APIs, microservices, event-driven systems.
Experience with databases (PostgreSQL, MySQL, MongoDB), GCP platform including BigQuery, GKE, Terraform, Docker, CI/CD pipelines, and strong testing fundamentals.
Experienced in building scalable, secure, and maintainable full-stack solutions integrating frontend, backend, cloud, and AI/ML components.
Comfortable working cross-functionally with Data Scientists, Product Managers, and Platform teams in modern cloud (GCP) and containerized environments.
Strong practical skills in modern web security, infrastructure as code, and operational excellence with focus on observability, performance, and reliability.