Google Cloud Platform Data Architect Multi-Cloud Assessment Engagement- Remote
Posted 4 days ago by Calance
Negotiable
Undetermined
Remote
Remote
Summary: The role of Google Cloud Platform Data Architect involves supporting a multi-cloud assessment for a major media enterprise, focusing on evaluating architectural options between Google Cloud Platform and Microsoft Azure. The architect will collaborate with an Azure Data Architect and a Management Consulting Strategy Lead to produce key artifacts that guide long-term platform decisions. The position requires extensive experience in Google Cloud data architecture and TCO modeling, with a strong emphasis on cross-platform integration and executive communication. This is a high-visibility, delivery-focused engagement aimed at optimizing cloud architecture for the client.
Key Responsibilities:
- Lead Google Cloud Platform-side architecture assessment, evaluating the client’s current BigQuery, GCS, and Airflow/dbt pipeline landscape.
- Drive TCO modeling for Google Cloud Platform, analyzing pricing structures and producing a defensible cost comparison against Azure/Fabric.
- Evaluate architectural patterns against the client’s use case requirements, including yield reporting and data integration.
- Define data movement and integration implications, assessing ingestion patterns and identifying egress cost risks.
- Collaborate cross-functionally with the Azure Data Architect to ensure equal analytical rigor across platforms.
- Support structured discovery by facilitating workshop-based sessions with client stakeholders.
- Document assumptions and guardrails, producing clear agreements for evaluation criteria.
Key Skills:
- 5+ years of hands-on Google Cloud Platform data architecture experience.
- Deep BigQuery expertise, including pricing models and IAM design.
- Experience with Google Cloud Platform data pipelines, including Apache Airflow and dbt.
- TCO modeling fluency, with the ability to build and defend cloud cost models.
- Multi-cloud architecture experience, particularly Google Cloud Platform-to-Azure integration.
- Strong executive communication skills for translating technical architecture into business frameworks.
- Experience in time-boxed consulting or assessment engagements.
- Power BI familiarity and knowledge of Row-Level Security in BigQuery.
- Understanding of Google Cloud Platform co-investment and ISV programs.
- Familiarity with media or ad-tech domains is a plus.
Salary (Rate): £100/hr
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
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)