Key Responsibilities :

A. Google Cloud Platform (GCP) Architecture & Development :

- Design, develop, and implement scalable cloud-native applications using Google Cloud Platform.

- Lead cloud architecture design, implementation, and deployment.

- Build and manage cloud infrastructure using GCP services.

- Work extensively with BigQuery, Vertex AI, GKE, Cloud Run, and Cloud Functions.

- Ensure high availability, scalability, reliability, and security of cloud applications.

- Optimize cloud infrastructure for performance and cost efficiency.

- Implement cloud-native solutions using microservices and serverless architecture.

- Drive cloud migration, modernization, and infrastructure optimization initiatives.

B. GCP Technologies - Core Technical Expertise :

1. Google BigQuery :

- Design and manage scalable data warehouse solutions.

- Develop and optimize complex SQL queries.

- Implement data processing and analytics pipelines.

- Optimize query performance and manage large datasets.

- Work with data integration and reporting solutions.

2. Vertex AI :

- Develop and deploy AI/ML models using Vertex AI.

- Integrate AI/ML capabilities into cloud-based applications.

- Work with model deployment, monitoring, and management.

- Understand MLOps concepts and AI-driven application development.

3. Google Kubernetes Engine (GKE) :

- Design and manage containerized applications.

- Deploy and manage microservices using Kubernetes.

- Handle cluster management, scaling, and orchestration.

- Implement application deployment and container management strategies.

- Monitor application health and optimize cluster performance.

4. Google Cloud Run :

- Develop and deploy containerized applications.

- Build scalable serverless application solutions.

- Manage application deployments and scaling.

- Optimize application performance and resource utilization.

5. Google Cloud Functions :

- Develop event-driven and serverless applications.

- Build backend services and API integrations.

- Implement event-based processing workflows.

- Integrate cloud functions with other GCP services.

C. Application Development - React & Python :

- Lead frontend development using React.js.

- Develop scalable, responsive, and high-performance user interfaces.

- Build backend services and APIs using Python.

- Develop RESTful APIs and microservices.

- Integrate frontend applications with backend services.

- Ensure application security, performance, and maintainability.

- Follow coding standards, design patterns, and software engineering best practices.

D. Snowflake & Data Engineering :

- Work with Snowflake cloud data warehouse solutions.

- Design and optimize data pipelines and data integration processes.

- Integrate Snowflake with GCP services.

- Develop and optimize SQL queries.

- Support data warehousing, analytics, and reporting requirements.

- Ensure data quality, performance, and reliability.

E. Technical Leadership & Team Management :

- Lead and mentor a team of developers and engineers.

- Provide technical direction and guidance to the engineering team.

- Review architecture, code quality, and technical deliverables.

- Drive engineering best practices and development standards.

- Conduct technical discussions, design reviews, and code reviews.

- Collaborate with product managers, architects, and cross-functional teams.

- Participate in requirement analysis and technical solution design.

- Take ownership of technical delivery and project execution.

- Identify technical risks and drive resolution.

- Encourage innovation and continuous improvement within the R&D team.

F. DevOps, Monitoring & Performance Optimization :

- Implement CI/CD pipelines and automated deployment processes.

- Work with Docker and Kubernetes-based deployments.

- Implement application monitoring, logging, and alerting.

- Monitor cloud infrastructure performance and availability.

- Troubleshoot production issues and perform root cause analysis.

- Ensure security, compliance, and cloud governance standards.