Skip to main content
QuickHire

Notifications

You're all caught up

New updates, payments, and messages will land here as soon as they arrive.

Google Cloud Partner Consulting

Google Cloud Platform Consulting for Enterprise Transformation

We architect, migrate, and operate GCP environments that power mission-critical enterprise workloads. From GKE and BigQuery to Vertex AI and Apigee, our certified Google Cloud engineers deliver platforms built for scale, security, and operational excellence.

ISO 27001SOC 2 ReadyNDA Day 1MSA AvailableIP Protection

Get Matched in 10 Minutes

Fill in the details PM calls you back to confirm.

No spam. PM calls within 10 minutes during business hours.

500+
Enterprise Clients
10,000+
Engineers Deployed
50+
Countries Served
99.4%
CSAT Score
48h
Team Assembly

The Challenge

Enterprise cloud migrations stall without the right GCP expertise

Organizations moving to Google Cloud face complex architectural decisions, fragmented tooling, and skills gaps that delay time-to-value. Without experienced GCP guidance, teams underutilize platform capabilities, overspend on compute, and accumulate technical debt that compounds over time.

68%
of cloud migrations exceed budget without expert architecture guidance
42%
of GCP spend is wasted on oversized or idle resources
$3.2M
average cost of a poorly planned cloud migration for mid-size enterprises
3x
faster time-to-production with managed GCP landing zone and DevOps pipelines

Why QuickHire

Why Enterprises Choose QuickHire

01

Certified Google Cloud Partner

Our team holds Google Cloud Professional certifications across architecture, data engineering, ML, and security. We maintain active partnership status with access to Google engineering resources and early product roadmap insights.

02

Enterprise-Grade Architecture

We design GCP environments using Well-Architected Framework principles with multi-region resilience, zero-trust security, and governance automation. Every architecture decision is documented with rationale and trade-off analysis for your internal review.

03

Data and AI Leadership

Our data practice specializes in BigQuery, Dataflow, Pub/Sub, and Vertex AI to build intelligent, event-driven data platforms. We have delivered production ML pipelines across retail, financial services, and healthcare clients.

04

Security and Compliance First

Security controls are embedded from the landing zone design stage, not retrofitted after deployment. We implement VPC Service Controls, Security Command Center, and Binary Authorization to satisfy SOC 2, PCI DSS, HIPAA, and ISO 27001 audit requirements.

05

FinOps and Cost Governance

Our managed clients achieve 25 to 35 percent cost reductions within 90 days through rigorous FinOps practices, Committed Use Discount optimization, and automated rightsizing recommendations. Cost visibility is built into every platform from day one.

06

Continuous Operations Support

Our SRE-model managed operations service provides 24/7 platform reliability coverage with defined SLAs, proactive capacity management, and quarterly business reviews. We operate as a seamless extension of your engineering organization.

Challenges

Common Enterprise Pain Points

01

Fragmented GCP Adoption Without a Coherent Strategy

Many enterprises have individual teams adopting GCP independently, creating inconsistent security postures, duplicate tooling, and unmanageable cost sprawl. Without a unified landing zone and governance framework, the platform becomes harder to secure and more expensive to operate over time. Our engagements establish organizational guardrails that give teams autonomy while maintaining enterprise control.

02

Data Migration Complexity and Downtime Risk

Migrating petabytes of structured and unstructured data from on-premises systems or competing clouds to GCP involves complex dependency mapping, data fidelity validation, and cutover coordination. Poorly planned migrations result in data loss, extended downtime, and failed rollbacks that damage business continuity. Our structured migration methodology with live replication and automated reconciliation eliminates these risks.

03

Kubernetes Operational Overhead at Scale

GKE delivers significant flexibility for containerized workloads, but managing node pools, cluster upgrades, workload autoscaling, and network policies at enterprise scale requires specialized expertise. Teams without dedicated Kubernetes experience accumulate operational debt that manifests as availability incidents and security vulnerabilities. Our GKE managed service absorbs that complexity so your engineers can focus on application delivery.

04

Unrealized Value from BigQuery and Analytics Investments

Organizations frequently invest in BigQuery but fail to realize its full potential due to suboptimal schema design, uncontrolled slot usage, and absence of data governance. Query costs escalate while analytics teams wait for results that should arrive in seconds. Our BigQuery optimization engagements restructure data models, implement reservation strategies, and establish query governance policies that transform platform economics.

05

API Management Gaps Limiting Digital Integration

Enterprises scaling their API ecosystems encounter security vulnerabilities, traffic management failures, and developer experience gaps when API management is not systematically implemented. Apigee provides the enterprise-grade API gateway capability that GCP-native organizations require, but implementation demands architectural expertise in proxy design, security policy, and developer portal configuration that most teams lack internally.

Our Approach

A full-lifecycle GCP consulting practice built for enterprise scale

Our Google Cloud consulting practice covers every stage of the enterprise GCP journey - from initial strategy and landing zone design through migration execution, platform engineering, and ongoing managed operations. We bring certified expertise, proven delivery methodology, and a commitment to measurable business outcomes on every engagement.

01
GCP Strategy and Architecture
We develop cloud strategy roadmaps and detailed reference architectures tailored to your business model, compliance requirements, and engineering team capabilities. Every architecture is reviewed by senior Google Cloud architects before delivery.
02
Migration and Modernization
Our migration factory approach handles lift-and-shift, re-platform, and re-architecture workloads in parallel waves, using Database Migration Service, Storage Transfer Service, and Datastream for reliable, auditable data movement.
03
Platform Engineering and DevOps
We build GCP platform foundations including CI/CD pipelines, GitOps workflows, infrastructure-as-code with Terraform, and developer self-service capabilities that accelerate application team velocity from day one.
04
Managed GCP Operations
Our SRE-model operations service delivers 24/7 platform reliability, security event response, cost optimization, and continuous platform improvement under contractual SLAs aligned to your business criticality requirements.

Delivery Models

How We Deliver

GCP Assessment and Roadmap

A focused engagement delivering cloud readiness assessment, target-state architecture, and a prioritized migration roadmap with business case and TCO analysis.

Timeline
4 weeks
Team Size
2-3 architects
Full Migration and Platform Build

End-to-end engagement from landing zone deployment through workload migration, platform engineering, and handover to internal teams or our managed operations service.

Timeline
12-24 weeks
Team Size
5-10 engineers
Managed GCP Operations

Ongoing SRE-model managed service covering platform reliability, security operations, cost governance, and continuous optimization under defined monthly SLAs.

Timeline
Ongoing
Team Size
3-6 SREs

Capabilities

Technical Capability Matrix

Infrastructure and Compute
GKE Autopilot and StandardCompute Engine and Instance GroupsCloud Run and Cloud FunctionsCloud Load BalancingAnthos and GKE Enterprise
Data and Analytics
BigQuery and BigQuery MLDataflow and Apache BeamPub/Sub and EventarcDataform and dbtCloud Composer and Apache Airflow
AI and Machine Learning
Vertex AI PipelinesVertex AI Model RegistryVertex AI Feature StoreGemini API IntegrationDocument AI and Vision AI
Security and Networking
VPC Service ControlsSecurity Command CenterCloud Armor and WAFIdentity-Aware ProxyBinary Authorization

Engagement Models

How We Engage

Choose the model that fits your programme governance, budget cycle, and team structure.

01

Staff Augmentation

Engineers embed directly under your management.

Learn more →
02

Dedicated Developers

Full-time team aligned to your product roadmap.

Learn more →
03

Managed Teams

End-to-end delivery with SLA-backed outcomes.

Learn more →
04

Engineering Pods

Autonomous cross-functional pods per domain.

Learn more →
05

Offshore Dev Centre

Permanent engineering base in India. Full IP ownership.

Learn more →
06

Build-Operate-Transfer

We build and run it. You take ownership on schedule.

Learn more →

Our Process

From Discovery to Delivery

1

Discovery and Cloud Readiness Assessment

Week 1

We audit your current infrastructure, applications, data landscape, and team capabilities to establish a baseline and identify migration priorities, risks, and quick wins.

2

Architecture Design and Landing Zone

Weeks 2-4

Our architects deliver a detailed target-state GCP architecture and deploy your enterprise landing zone with organization hierarchy, networking, IAM, and security guardrails.

3

Migration Wave Planning and Pilot

Weeks 4-6

We sequence workloads into migration waves by complexity and criticality, execute a pilot migration with full validation, and refine the migration runbook for subsequent waves.

4

Full Migration and Platform Engineering

Weeks 6-20

Migration waves execute in parallel with platform engineering workstreams building CI/CD pipelines, observability stacks, and developer tooling to accelerate application team onboarding.

5

Optimization and Managed Operations

Ongoing

Post-migration, we optimize cost, performance, and reliability continuously, transitioning to our managed operations service or conducting structured knowledge transfer to your internal team.

Free Scoping Call

Not ready to book? Our PM calls back.

Tell us what's broken. We'll scope it for free and confirm the right expert no commitment.

PM available now

Get a fix plan
in 10 minutes.

No sales call. A real PM scopes your problem, recommends the right expert, and gives you the plan only book if it fits.

  • Free scoping call PM explains exactly how we fix it
  • No commitment hear the plan before you pay anything
  • Expert confirmed right skill match for your stack
R
P
A

47 PMs responded today

Get Matched in 10 Minutes

Fill in the details PM calls you back to confirm.

No spam. PM calls within 10 minutes during business hours.

Security & Compliance

Enterprise-Grade Security by Default

✓ISO 27001 Certified✓SOC 2 Type II Ready✓GDPR Compliant✓DPDP Act Ready✓NDA on Day 1✓MSA Available✓IP Assignment Clauses✓Escrow Options

Governance

Programme Governance

✓

Weekly Engineering Standups

Weekly syncs with your technical stakeholders review sprint progress, blockers, and upcoming decisions. All meeting notes and action items are tracked in your project management tool.

✓

Architecture Decision Records

Every significant architectural decision is documented as an Architecture Decision Record capturing the context, options considered, decision rationale, and trade-offs for future reference.

✓

Security and Compliance Review Gates

Pre-defined review gates at landing zone completion, pilot migration, and production cutover ensure security controls and compliance requirements are verified before advancing to the next phase.

✓

Monthly Business Reviews

Executive-level monthly reviews present platform health metrics, cost trends, migration progress against plan, and upcoming roadmap decisions requiring business input.

Team Structure

Your Enterprise Team

Our GCP delivery teams are composed of Google Cloud certified professionals drawn from our cloud architecture, data engineering, security, and SRE practices. Each engagement is staffed with a dedicated Technical Lead who serves as your primary point of accountability throughout the engagement lifecycle and beyond.

✓GCP Solutions Architect
✓Cloud Infrastructure Engineer
✓GKE Platform Engineer
✓BigQuery Data Engineer
✓Vertex AI ML Engineer
✓Cloud Security Engineer
✓DevOps and CI/CD Engineer
✓SRE and Operations Lead

Project Lifecycle

From Kickoff to Production

01
2-4 weeks

Strategy and Assessment

Cloud readiness report, TCO analysis, target-state architecture blueprint, migration roadmap with prioritized workload inventory.

02
3-5 weeks

Foundation and Landing Zone

GCP organization hierarchy, VPC and network topology, IAM framework, Organization Policy constraints, Terraform modules, security baseline.

03
8-16 weeks

Migration Execution

Migrated workloads by wave, data validation reports, cutover runbooks, post-migration performance benchmarks.

04
4-8 weeks

Platform Engineering

CI/CD pipelines, observability dashboards, developer self-service portal, runbooks, and operational documentation.

05
Ongoing

Managed Operations

Monthly SLA reports, cost optimization recommendations, quarterly business reviews, security posture reports, platform release notes.

Case Studies

Enterprise Outcomes

Financial Services

A regional bank needed to migrate 200+ legacy applications to GCP with zero tolerance for data loss or regulatory non-compliance.

We designed a phased migration strategy with live database replication via Datastream and implemented VPC Service Controls and CMEK encryption to satisfy PCI DSS requirements.

99.99%uptime maintained across all production workloads during migration
Retail

A global retailer struggled with BigQuery costs exceeding $2M annually due to uncontrolled ad-hoc query patterns and inefficient schema design.

We restructured data models with partitioning and clustering, implemented slot reservations and query cost controls, and delivered Looker dashboards for real-time cost visibility by department.

$800Kannual BigQuery cost reduction within six months of optimization engagement
Healthcare

A health system required a HIPAA-compliant Vertex AI platform to operationalize predictive models for patient readmission risk.

We deployed Vertex AI Pipelines with de-identified training data workflows, implemented audit logging satisfying HIPAA requirements, and integrated model outputs into the clinical workflow via a Cloud Run API layer.

23%reduction in 30-day readmission rates attributed to model-guided interventions

Start Your Engagement

Ready to Build Your Enterprise Engineering Team?

Speak with a solution architect. We scope your engagement together. No sales pressure, no commitment required.

Hiring Models

One platform, two ways to hire

Not ready for a long-term commitment? QuickHire Instant lets you book a vetted engineer in 10 minutes - no contracts required.

Both models use the same vetted talent network · PM always included · Multi-country billing

Frequently Asked Questions

Our GCP consulting engagements begin with a thorough discovery and cloud readiness assessment, where we audit your existing infrastructure, workloads, and data architecture. We then design a target-state GCP architecture aligned with your business objectives and compliance requirements. Delivery spans migration execution, platform engineering, security hardening, and cost optimization. Post-launch, our managed operations team handles ongoing monitoring, incident response, and continuous platform improvement.
We follow Google Cloud Well-Architected Framework principles across five pillars: operational excellence, security, reliability, performance efficiency, and cost optimization. Every architecture design includes landing zone setup with appropriate VPC configurations, IAM hierarchies, and organizational policies. We design for multi-region resilience where business continuity requirements demand it. Our architects also incorporate observability from day one, using Cloud Monitoring, Cloud Trace, and Cloud Logging to provide full-stack visibility.
Our engineering team has deployed and managed GKE clusters supporting thousands of production pods across regulated industries including financial services and healthcare. We design GKE environments with Autopilot or Standard mode depending on team maturity and cost profiles, incorporating Workload Identity, Binary Authorization, and GKE Security Posture Management. We implement GitOps pipelines using Cloud Build and Artifact Registry to enforce consistent, auditable deployments. Our GKE engagements consistently achieve 99.9% or higher cluster availability through proactive node management and controlled upgrade strategies.
We design BigQuery environments that balance query performance, cost governance, and data governance across enterprise data estates. This includes slot reservation strategies, partitioning and clustering schemes optimized for your query patterns, and row-level security policies aligned with data sensitivity classifications. We integrate BigQuery with Dataform or dbt for transformation orchestration and implement Data Catalog for metadata management and lineage tracking. Our clients routinely see 40 to 70 percent reductions in query costs after our optimization engagements.
Yes, Vertex AI is a core capability within our AI and data practice. We implement end-to-end ML pipelines using Vertex AI Pipelines, Model Registry, and Feature Store to create reproducible, governed model development workflows. For generative AI use cases, we build solutions on Vertex AI Model Garden and Gemini APIs, integrating grounding with enterprise data via Vertex AI Search. Our MLOps practice ensures models are monitored for drift, retrained on schedule, and promoted through staging environments before production release. We have delivered Vertex AI solutions across demand forecasting, document intelligence, fraud detection, and customer personalization domains.
Cloud Run is our preferred deployment target for stateless microservices, event-driven processors, and API backends that require rapid scaling without infrastructure overhead. We design Cloud Run architectures with appropriate concurrency settings, minimum instance configurations to eliminate cold-start latency for latency-sensitive workloads, and VPC connector integrations for private resource access. We connect Cloud Run services to Eventarc, Pub/Sub, and Cloud Tasks for resilient asynchronous processing patterns. Our serverless designs typically reduce operational overhead by 60 percent compared to equivalent VM-based deployments.
We implement Apigee X and Apigee hybrid as the API gateway layer for organizations standardizing on GCP-native API management. Our Apigee practice covers proxy design, traffic management policies, OAuth 2.0 and API key security, developer portal configuration, and monetization enablement for API product lines. We integrate Apigee with Cloud Armor for DDoS protection and Cloud Logging for full API traffic observability. For enterprise migrations from legacy API gateways, we provide structured runbooks that migrate existing proxies with zero business disruption.
Our data migration process begins with a comprehensive data inventory and classification exercise to map sources, volumes, sensitivity levels, and dependencies. We use Storage Transfer Service, Database Migration Service, and Datastream for live replication depending on source systems and acceptable downtime windows. For complex heterogeneous environments, we build custom migration orchestration using Cloud Composer to sequence and validate every migration batch. Post-migration validation includes row count reconciliation, checksum verification, and performance benchmarking against the source system before cutover approval.
Google Workspace integration enables unified identity, collaboration, and data workflows across enterprise GCP deployments. We implement Cloud Identity as the authoritative identity provider, synchronizing with existing Active Directory or LDAP systems via Google Cloud Directory Sync. Application integrations include Workspace APIs for Gmail, Drive, Calendar, and Meet embedded within custom enterprise applications and approval workflows. We also configure Drive for desktop and Shared Drives with DLP policies enforced through Google Workspace DLP and Cloud DLP to protect sensitive content across collaboration surfaces.
Our GCP security practice implements controls mapped to SOC 2, ISO 27001, PCI DSS, HIPAA, and FedRAMP depending on client compliance requirements. We establish Organization Policy constraints to enforce guardrails at scale, deploy VPC Service Controls to create data perimeters around sensitive resources, and configure Security Command Center Premium for continuous threat detection. Identity-centric zero-trust access is implemented using Identity-Aware Proxy and BeyondCorp Enterprise. Every engagement includes a shared responsibility matrix that clearly delineates which controls Google manages versus client obligations.
Cost governance begins at the architecture stage by right-sizing compute, selecting appropriate storage classes, and designing autoscaling policies to eliminate idle resource spend. We implement billing export to BigQuery with Looker Studio dashboards that provide department-level cost visibility and anomaly alerts. Committed Use Discounts and Sustained Use Discount optimization is performed quarterly alongside Recommender API analysis to identify underutilized resources. Our managed clients typically achieve 25 to 35 percent cost reductions within the first 90 days through a structured FinOps program.
We design GCP landing zones using the Google Cloud Enterprise Foundation Blueprint as a baseline, customized for each organization's governance model, network topology, and team structure. The landing zone establishes resource hierarchy with folders for production, non-production, and shared services environments, enforces Organization Policy constraints, and provisions shared VPCs with centralized network administration. Terraform modules managed in Cloud Source Repositories or GitHub ensure every environment configuration is version-controlled and reproducible. We deliver landing zones that teams can begin populating within two weeks of engagement kickoff.
We design disaster recovery architectures on GCP aligned to defined Recovery Time Objective (RTO) and Recovery Point Objective (RPO) targets negotiated with business stakeholders. For mission-critical systems, we implement active-active multi-region configurations using Global Load Balancing, Cloud Spanner, or Bigtable replication depending on data consistency requirements. Warm standby and pilot light patterns are deployed for workloads with more relaxed RTO requirements, using Cloud Storage cross-region replication and automated failover runbooks. We conduct annual DR drills with documented evidence packages suitable for audit review.
Our GCP DevOps practice centers on Cloud Build for CI pipelines, Artifact Registry for container and artifact storage, and Cloud Deploy for managed continuous delivery with approval gates and rollback capabilities. We integrate Cloud Build with GitHub, GitLab, or Bitbucket via native triggers, implementing trunk-based development workflows with automated testing, security scanning, and container vulnerability analysis. For complex multi-environment deployments, we layer Terraform Cloud or Atlantis for infrastructure promotion alongside application delivery pipelines, providing a single pane of glass for change management.
Our managed GCP operations service provides a dedicated SRE team that assumes responsibility for platform reliability, security patching, capacity planning, and incident response under defined SLAs. The service includes 24/7 alerting coverage with on-call rotation, monthly infrastructure reviews with optimization recommendations, and quarterly business reviews that align platform performance to business outcomes. We operate as an extension of your internal engineering team, participating in your change management and incident management processes using your existing ITSM tooling such as ServiceNow or Jira Service Management. Engagements are structured as monthly retainers with defined escalation paths and guaranteed response times.
Many enterprise clients operate heterogeneous cloud environments, and our architects design integration patterns that allow GCP to coexist with AWS or Azure without creating operational complexity or security gaps. We implement consistent networking using interconnects or VPNs, unified identity federation, and centralized logging aggregation that spans clouds to give security and operations teams a single view. For workloads that span clouds, we evaluate data gravity, egress cost implications, and latency requirements to make workload placement decisions grounded in total cost of ownership analysis. Our multi-cloud governance frameworks include tagging standards, cost allocation methodologies, and policy enforcement tooling that applies consistently regardless of the underlying cloud provider.
Industries
Financial ServicesHealthcareRetailMedia and EntertainmentTechnology