Sr. Google Cloud Engineer Experience

Sr. Google Cloud Engineer
Experience: 7+ years
Job Type: Fulltime
Location: Chennai

Role Overview
We are seeking a Sr. Google Cloud Engineer with strong handson expertise in designing, building, and operating scalable, highly available, secure, and disasterrecoveryready infrastructure on Google Cloud Platform (GCP).

This is a senior infrastructure engineering role focused on GCP Landing Zone design and implementation, networking and security, identity and access management, platform services, automation through IaC, and capacity optimization.

The role supports enterprise workloads including cloudnative applications, CI/CD platforms, data & analytics systems, eventdriven architectures, and AI/ML workloads.

Key Responsibilities
Cloud Architecture & Landing Zone

• Design and implement scalable, highly available, and DRready GCP infrastructure

• Own GCP Landing Zone design and implementation, including:

• Resource hierarchy (Org, Folders, Projects)

• Shared VPC architecture and network segmentation

• Security guardrails, governance, and standards

• Define best practices for multiproject and multienvironment GCP architectures

Networking, Private Connectivity & Security

• Design and operate secure private connectivity patterns, including:

• Private Service Connect (PSC)

• Private Service Access (PSA)

• Design, build, and operate GCP networking, including:

• VPCs, subnets, routing, firewall rules

• Cloud Routers

• HA VPN

• Hybrid connectivity (onprem GCP)

• Implement Serverless VPC Access for Cloud Run and other serverless workloads

• Design and manage Cloud DNS

• Configure log sinks and log router pipelines for centralized logging and compliance

Identity, Security & Governance

• Implement and manage IAM, including:

• Service Accounts

• Leastprivilege role design

• Workload Identity

• Implement advanced security controls:

• VPC Service Controls (VPCSC)

• IdentityAware Proxy (IAP)

• Cloud Armor (WAF & DDoS protection)

• Binary Authorization

• Model Armor for AI/ML workloads

• Manage encryption and secrets using Cloud KMS / Key Rings

• Design and integrate infrastructurelevel Palo Alto NGFW in GCP

Certificates, TLS & Access

• Design and implement TLS/SSL certificate lifecycle management using:

• Google Certificate Manager

• Managed and selfmanaged certificates

• Ensure secure ingress for load balancers, GKE, and Cloud Run workloads

Compute, Serverless & CI/CD Platforms

• Provision and operate:

• Compute Engine

• GKE (Google Kubernetes Engine)

• Cloud Run

• Design and implement enterprise GitLab infrastructure, including HA, DR, security, and backups

• Manage Artifact Registry for container images and build artifacts

Data, Messaging & Analytics

• Design and operate:

• Cloud SQL

• AlloyDB

• BigQuery

• Firestore

• Firebase

• Google Cloud Storage (GCS)

• Build data pipelines using Dataflow

• Design eventdriven and asynchronous architectures using:

• Pub/Sub

• Eventarc

• Cloud Tasks

• Cloud Scheduler

• Design and operate API platforms using Apigee

Caching, AI/ML & Performance

• Design and manage inmemory caching using Memorystore (Redis)

• Support highperformance workloads, including:

• GSUs

• GPUbased compute

• Enable and support AI/ML platforms, including:

• Vertex AI

• LLM model hosting and integrations

• Drive capacity planning and optimization to ensure scalability, performance, and cost efficiency

Infrastructure Automation, Operations & Governance

• Design, implement, and operate a selfhosted OpenTofu (Opensource Terraform) platform for Infrastructure as Code (IaC)
• Build and manage IaC pipelines using Terraform and OpenTofu
• Troubleshoot and resolve complex infrastructure issues across networking, security, compute, data, and platform services
• Design and implement OS patching strategies, including automation and compliance
• Design and implement enterprise backup and disaster recovery strategies
• Participate in incident, problem, and change management processes
• Provide operational support for production and nonproduction environments
• Drive knowledge sharing and team enablement through training, documentation, and walkthroughs
• Maintain architecture documentation, standards, runbooks, and SOPs

Required Technical Skills

• Google Cloud Platform (GCP)
• Landing Zone architecture & implementation
• IAM, Service Accounts, Workload Identity
• Private Service Connect (PSC), Private Service Access (PSA)
• Serverless VPC Access
• VPC Service Controls, IAP, Cloud Armor, Binary Authorization
• Cloud KMS / Key Rings
• Palo Alto NGFW
• VPC, Cloud Router, HA VPN, Cloud DNS
• Certificate Manager / TLS lifecycle
• Compute Engine, GKE, Cloud Run
• GitLab, Artifact Registry
• Firestore, Firebase
• BigQuery, Dataflow, Looker
• Pub/Sub, Eventarc, Cloud Tasks, Cloud Scheduler
• Apigee
• Memorystore (Redis)
• Vertex AI, LLM models
• Backup & DR architecture
• Capacity optimization
• Terraform, OpenTofu
• Linux / Unix
• Python, Bash
• Cloud Monitoring, Logging, Log Sinks

Soft Skills

• Strong cloud architecture and systemsthinking mindset
• Ability to design for scale, availability, security, and DR
• Excellent communication and documentation skills
• High ownership and accountability
• Strong collaboration across Team (App,DevOps,SRE &InfoSec)
• Proactive, automationfirst, continuousimprovement mindset

Qualifications & Experience

• Bachelors or Masters degree in Computer Science, Engineering, or equivalent experience
• 7+ years of experience in Cloud Engineering, Infrastructure Engineering, or Platform Engineering
• Proven experience managing enterprisescale GCP environments
• Strong experience designing HA, DR, and secure cloud platforms

Preferred Qualifications

• Google Cloud Professional certifications (Cloud Architect, DevOps Engineer)
• Experience in regulated or large enterprise environments
• Multiproject and multiregion GCP experience
• Exposure to FinOps / cloud cost optimization
• Familiarity with Agile / Scrum methodologies