V
Architect
Job Description
Role
Google Cloud Architect
Experience
Typically 8–15+ years of overall IT experience, with significant experience designing and implementing enterprise cloud solutions. Strong hands-on Google Cloud experience is expected for senior roles.
Key Responsibilities
Design enterprise-scale Google Cloud architectures aligned with business and technical requirements.
Develop cloud adoption, modernization, migration, and transformation strategies.
Design highly available, scalable, resilient, secure, and cost-optimized solutions.
Lead migration of applications and infrastructure from on-premises/AWS/Azure to Google Cloud.
Define architecture for compute, networking, storage, databases, containers, integration, analytics, and security.
Design and implement GCP landing zones, organization/folder/project structures, IAM and governance.
Design enterprise networking using VPC, Shared VPC, Cloud Load Balancing, Cloud NAT, Cloud VPN, Cloud Interconnect and hybrid connectivity.
Architect containerized applications using GKE, Cloud Run and Artifact Registry.
Design data platforms using services such as BigQuery, Cloud Storage, Pub/Sub, Dataflow, Cloud SQL, Spanner and Bigtable, according to workload requirements.
Implement security architecture using IAM, KMS, Secret Manager, Security Command Center, VPC Service Controls and organizational policies.
Define high availability, disaster recovery, backup and business continuity strategies.
Establish observability using Cloud Logging, Cloud Monitoring, tracing and alerting.
Drive Infrastructure as Code using Terraform and automated deployment through CI/CD.
Perform architecture reviews, identify technical risks and recommend remediation.
Optimize workloads for performance, reliability and cloud cost.
Work with engineering, security, networking, DevOps, data and business teams to deliver cloud solutions.
Produce architecture diagrams, HLD/LLD documents, migration plans and technical proposals.
Provide technical leadership and mentor cloud engineers and architects.
Core Technical Skills
Google Cloud
Compute Engine
GKE
Cloud Run
Cloud Functions
Cloud Storage
VPC / Shared VPC
Cloud Load Balancing
Cloud DNS
Cloud NAT
Cloud VPN
Cloud Interconnect
Cloud IAM
Cloud KMS
Secret Manager
Cloud Monitoring / Logging
BigQuery
Pub/Sub
Dataflow
Cloud SQL
Google Cloud Architect
Experience
Typically 8–15+ years of overall IT experience, with significant experience designing and implementing enterprise cloud solutions. Strong hands-on Google Cloud experience is expected for senior roles.
Key Responsibilities
Design enterprise-scale Google Cloud architectures aligned with business and technical requirements.
Develop cloud adoption, modernization, migration, and transformation strategies.
Design highly available, scalable, resilient, secure, and cost-optimized solutions.
Lead migration of applications and infrastructure from on-premises/AWS/Azure to Google Cloud.
Define architecture for compute, networking, storage, databases, containers, integration, analytics, and security.
Design and implement GCP landing zones, organization/folder/project structures, IAM and governance.
Design enterprise networking using VPC, Shared VPC, Cloud Load Balancing, Cloud NAT, Cloud VPN, Cloud Interconnect and hybrid connectivity.
Architect containerized applications using GKE, Cloud Run and Artifact Registry.
Design data platforms using services such as BigQuery, Cloud Storage, Pub/Sub, Dataflow, Cloud SQL, Spanner and Bigtable, according to workload requirements.
Implement security architecture using IAM, KMS, Secret Manager, Security Command Center, VPC Service Controls and organizational policies.
Define high availability, disaster recovery, backup and business continuity strategies.
Establish observability using Cloud Logging, Cloud Monitoring, tracing and alerting.
Drive Infrastructure as Code using Terraform and automated deployment through CI/CD.
Perform architecture reviews, identify technical risks and recommend remediation.
Optimize workloads for performance, reliability and cloud cost.
Work with engineering, security, networking, DevOps, data and business teams to deliver cloud solutions.
Produce architecture diagrams, HLD/LLD documents, migration plans and technical proposals.
Provide technical leadership and mentor cloud engineers and architects.
Core Technical Skills
Google Cloud
Compute Engine
GKE
Cloud Run
Cloud Functions
Cloud Storage
VPC / Shared VPC
Cloud Load Balancing
Cloud DNS
Cloud NAT
Cloud VPN
Cloud Interconnect
Cloud IAM
Cloud KMS
Secret Manager
Cloud Monitoring / Logging
BigQuery
Pub/Sub
Dataflow
Cloud SQL
More Info
Key Skills
Cloud Logging
Cloud Functions
GKE
Cloud NAT
Cloud Interconnect
Cloud DNS
VPC Shared VPC
Cloud Monitoring
Cloud Run
Cloud KMS
Cloud Load Balancing
Cloud SQL
Cloud IAM
Secret Manager
Cloud VPN
About Company
Skills:
SAP, Networking, Storage, Microsoft 365, SFDC, network bring-up, cloud-scale programs, AI platforms, facility readiness, rack integration, large-scale infrastructure, enterprise cloud programs, Wrike, Teams, customer-facing coordination, structured executive updates, HPC deployment lifecycles, Compute, GPU validation, data center systems, accelerated computing systems, liquid cooling commissioning, technical delivery, Sharepoint, engagement leadership
Skills:
data masking , snowflake , Single Sign-On (SSO), Role-Based Access Control (RBAC), Data Modelling, Power Bi, DevSecOps, Azure, Auditing, Data Ingestion, Entra ID, Azure Private Networking, Snowflake Secure Data Sharing, Medallion Architecture, Data Platform Architecture, SCIM, PrivateLink, Snowpark, data classification, Streamlit, Cloud Storage Services, Cortex AI, CI/CD Pipelines, Network Policies
Skills:
Ml, Streaming, Pyspark, Sql, Spark, Python, Lakehouse design patterns, Cloud-native platforms, Distributed systems at scale, Enterprise data architecture, Data governance frameworks, Ai, Databricks Platform, Real-time systems
Skills:
Java, Apis, Cloud Services, Integrations, Software Engineering, Python, Sql, Relational Databases, Architecture Design
Skills:
Sql, MLops, Cloud Architecture, Docker, Kubernetes, Python, Azure DevOps, Generative AI, enterprise data architecture, LLMOps, GitHub Actions, RAG, AI-ready data platforms, AI agents, AI security and governance