Data Architect - GCP Cloud
Listed on 2026-10-30
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IT/Tech
Data Engineering, Cloud Computing: Infrastructure & Operations, Data Warehousing
Location
- Remote (Travel to NY on need Basis)
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- 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
Architect solutions using:
- Big Query
- Dataflow
- Pub Sub
- Dataplex
- Data Catalog
- Cloud Functions
- Define storage partitioning clustering and optimization strategies
- Establish enterprise data interoperability patterns
- Lead migration from legacy platforms such as Snowflake Hadoop Teradata Oracle or AWSbased ecosystems to GCP
- Databases
- APIs
- SaaS Platforms
- Streaming Sources
- Enable batch incremental CDC and realtime architectures
- Design Iceberg based Lakehouse solutions
- Governance Security Compliance
- Implement data lineage cataloging metadata management and stewardship processes
- IAM
- VPC
- Service Accounts
- KMS
- Ensure compliance with data privacy security and audit requirements
- Design cost efficient cloud architectures
- Optimize Big Query consumption and storage costs
- Improve processing performance across Dataflow and Dataproc workloads
- Establish Fin Ops and monitoring practices
- Engage with business and technology leadership
- Convert business requirements into target state architectures
- Lead workshops discovery sessions and architecture reviews
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