GCP Data Solution Architect

Role - Google Data Solution Architect

Location- Remote (Travel to Newyork on need Basis)

Role Summary

The GCP Data Solution Architect is responsible for designing and governing enterprise scale data platforms on Google Cloud The role will define target state architectures establish reusable data patterns and frameworks guide migration and modernization initiatives and ensure secure scalable and cost-efficient delivery of data products and analytics solutions

The architect will collaborate with business stakeholder’s product owners data engineers data modelers governance teams and cloud platform teams to deliver a modern Lakehouse architecture supporting analytics AIML and business intelligence workloads This aligns with enterprise expectations for scalable architectures reusable patterns data product models and trusted data catalog capabilities GCP Data P9 May 2026 Word GCP Data Approved Word

Key Responsibilities

Architecture Solution Design

• Define enterprise scale GCP data platform architecture
• Design Lakehouse architectures leveraging Medallion principles Bronze Silver Gold
• Create scalable reusable data product and domain driven architecture patterns
• Design meta data driven ingestion frameworks and data processing architectures
• Develop reference architectures design standards and implementation blueprints
• Lead architecture reviews and technical governance boards

Cloud Data Platform

Architect solutions using:

• BigQuery
• Cloud Storage GCS
• Dataproc
• Dataflow
• PubSub
• Cloud Composer
• Dataplex
• Data Catalog
• Vertex AI
• Cloud Functions
• Cloud Run
• Define storage partitioning clustering and optimization strategies
• Establish enterprise data interoperability patterns
• Data Engineering Modernization
• Lead migration from legacy platforms such as Snowflake Hadoop Teradata Oracle or AWSbased ecosystems to GCP
• Define ingestion strategies for
• Databases
• APIs
• SaaS Platforms
• Streaming Sources
• Files CSV Parquet Excel
• Enable batch incremental CDC and realtime architectures
• Design Icebergbased Lakehouse solutions
• Governance Security Compliance
• Define enterprise data governance standards
• Implement data lineage cataloging metadata management and stewardship processes

Design secure architectures using

• IAM
• VPC
• Service Accounts
• KMS
• Secret Manager
• Ensure compliance with data privacy security and audit requirements

Performance Cost Optimization

• Design costefficient cloud architectures
• Optimize BigQuery consumption and storage costs
• Improve processing performance across Dataflow and Dataproc workloads
• Establish FinOps and monitoring practices

Stakeholder Leadership

• Engage with business and technology leadership
• Convert business requirements into target state architectures
• Lead workshops discovery sessions and architecture reviews