Google Cloud Platform Data Architect Multi-Cloud Assessment Engagement- Remote

About the Engagement
Looking for a Google Cloud Platform Data Architect to support a time-boxed multi-cloud assessment for a major media enterprise. The client operates a production Google Cloud Platform environment including BigQuery, Airflow-based pipelines, and Google Cloud Storage alongside a Microsoft Azure/Fabric footprint. The engagement objective is to evaluate architectural options across both platforms, deliver a defensible Total Cost of Ownership (TCO) comparison, and produce a recommended architecture direction to guide long-term platform decisions.
This is a high-visibility, delivery-focused engagement. You will work alongside an Azure Data Architect and a Management Consulting Strategy Lead to produce three core artifacts: an Architectural Decision Framework, a Cloud Economic Lever Analysis, and a Recommended Architecture Direction & Guardrails document.

What You ll Do
Lead Google Cloud Platform-side architecture assessment evaluate the client s current BigQuery, GCS, and Airflow/dbt pipeline landscape through targeted working sessions and existing documentation review
Drive TCO modeling for Google Cloud Platform analyze BigQuery slot reservation pricing, committed use discount structures, Google Cloud Platform co-investment programs, and cross-cloud egress costs to produce a defensible cost comparison against Azure/Fabric
Evaluate architectural patterns assess BigQuery-first consolidation, Fabric-light federated, and Looker-abstracted hybrid approaches against the client s use case requirements, including holistic yield reporting, cross-division dashboarding, and addressable TV/Linear data integration
Define data movement and integration implications assess ingestion patterns across Google Cloud Platform-native pipelines (GAM log processing, Google Analytics, Conviva/OTT, Braze, Sailthru, Supermetrics) and identify egress cost risk at scale
Collaborate cross-functionally work in lockstep with the Azure Data Architect (counterpart role) to ensure both platforms are evaluated with equal analytical rigor and that integration seams are clearly defined
Support structured discovery develop and facilitate workshop-based discovery sessions with client Google Cloud Platform architects, engineers, and finance stakeholders to validate assumptions and document cost inputs
Document assumptions and guardrails produce clear, agreed-upon assumptions for each evaluation criterion and flag areas requiring empirical validation beyond this engagement s scope

What You Bring
Required
5+ years of hands-on Google Cloud Platform data architecture experience with production deployments at scale
Deep BigQuery expertise slot reservation and commitment models, on-demand vs. capacity pricing, partitioning/clustering strategies, and cross-project IAM design
Google Cloud Platform data pipeline experience Apache Airflow (Cloud Composer), dbt, and GCS-based data movement patterns in production environments
TCO modeling fluency demonstrated ability to build and defend cloud cost models, including egress analysis, compute-to-storage ratios, and negotiated pricing structures (ELA/committed use discounts)
Multi-cloud architecture experience familiarity with Google Cloud Platform-to-Azure integration patterns, cross-cloud egress cost implications, and data federation strategies
Strong executive communication skills ability to translate technical architecture trade-offs into business-readable frameworks for CDO/VP-level stakeholders
Experience operating in time-boxed consulting or assessment engagements comfort with directional outputs, documented assumptions, and rapid iteration

Preferred
Power BI familiarity understanding of how Power BI connects to BigQuery via ODBC gateway and where latency/performance trade-offs emerge vs. native Fabric semantic models
Row-Level Security (RLS) experience knowledge of RLS implementation patterns in BigQuery and how they compare to Fabric/Power BI Premium semantic model RLS
Google Cloud Platform co-investment and ISV program knowledge familiarity with Google s commercial programs (committed use, co-investment, MSA structures) that affect total cost at enterprise scale
Media or ad-tech domain experience familiarity with GAM, ad log pipelines, or audience data platforms is a plus given the client s industry

Engagement Context: Tools & Platforms In Scope

Platform
Components
Google Cloud Platform
BigQuery, Google Cloud Storage (GCS), Cloud Composer (Airflow), dbt
Source Systems (Google Cloud Platform-native)
Google Ad Manager (GAM), Google Analytics (GA), Conviva/OTT, Braze, Sailthru, Supermetrics
Azure / Microsoft
Synapse dedicated SQL pool, Microsoft Fabric, Power BI Premium
Source Systems (Azure-native)
AnyScreen, WideOrbit, AdBook, Dynamics CRM
BI Layer
Power BI (cross-platform), Looker (evaluation only)