Google Cloud Analytics Engineer – Web Application

Position - Google Cloud Analytics Engineer – Web Application

Location - United States

Duration - Long-term

Job Summary

We are seeking an experienced Google Cloud Analytics Engineer with expertise in Google Cloud Platform (GCP), data engineering, analytics, and web application development. The candidate will design, develop, and maintain scalable cloud-based analytics solutions and web applications that enable business intelligence, data visualization, and data-driven decision-making.

The ideal candidate will have hands-on experience with Google BigQuery, Cloud Storage, Dataflow, Looker, SQL, Python, APIs, and modern web application frameworks.

Key Responsibilities

Google Cloud & Data Analytics

• Design, develop, and maintain data pipelines using Google Cloud Platform services.
• Build and optimize analytical data models and SQL queries in BigQuery.
• Develop ETL/ELT pipelines using Dataflow, Cloud Composer, Dataform, or similar technologies.
• Integrate data from databases, REST APIs, enterprise systems, and external data sources.
• Implement data quality checks, data validation, and monitoring.
• Develop dashboards and reports using Looker, Looker Studio, or other BI tools.
• Optimize query performance, storage utilization, and cloud costs.
• Implement data governance, security, access controls, and compliance standards.

Web Application Development

• Design and develop web applications that consume and display analytics data.
• Build responsive front-end interfaces using React, Angular, or similar frameworks.
• Develop backend services and REST APIs using Python, Node.js, Java, or equivalent technologies.
• Integrate web applications with BigQuery and other Google Cloud services through secure backend services.
• Develop interactive dashboards, reports, data visualizations, and analytics portals.
• Implement authentication and authorization using Google Cloud Identity services or Identity Platform.
• Deploy and manage web applications using Cloud Run, App Engine, Firebase Hosting, or Google Kubernetes Engine.
• Ensure application performance, scalability, security, and reliability.

DevOps & Production Support

• Build CI/CD pipelines using Cloud Build, GitHub Actions, or similar tools.
• Use Terraform or other Infrastructure as Code tools to manage cloud resources.
• Monitor applications and data pipelines using Cloud Monitoring and Cloud Logging.
• Troubleshoot production issues and improve system reliability.
• Collaborate with business analysts, data engineers, architects, and product teams.

Required Technical Skills

• Google Cloud Platform: BigQuery, Cloud Storage, Cloud Run, IAM, Cloud Logging, and Cloud Monitoring.
• Data Engineering: SQL, Python, ETL/ELT, data modeling, and pipeline development.
• Analytics & BI: Looker, Looker Studio, dashboard development, and KPI reporting.
• Web Development: JavaScript/TypeScript, React or Angular, HTML5, and CSS3.
• Backend Development: Python, Node.js, Java, or similar technologies.
• API Integration: REST APIs, JSON, OAuth 2.0, and service-to-service authentication.
• DevOps: Git, CI/CD, Docker, and Terraform.
• Database Technologies: BigQuery, PostgreSQL, MySQL, or equivalent relational databases.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
• 5+ years of experience in software development, data engineering, cloud analytics, or a related discipline.
• 3+ years of hands-on experience with Google Cloud Platform.
• Experience developing and deploying production-grade web applications.
• Strong understanding of data warehousing, dimensional modeling, and analytics architecture.
• Experience implementing role-based access control and securing sensitive data.
• Google Cloud Professional Data Engineer or Professional Cloud Developer certification is a plus.

Key Deliverables

• Scalable Google Cloud analytics architecture.
• Automated and reliable data ingestion and transformation pipelines.
• BigQuery datasets, views, and optimized analytical data models.
• Web-based analytics portal with interactive dashboards.
• Secure APIs connecting the web application to cloud analytics services.
• CI/CD pipelines, monitoring, technical documentation, and production support.

Success Criteria

• Reliable and timely delivery of analytical data.
• High-performing and responsive web application.
• S…