Google Cloud Platform Data Architect

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Designs and implements scalable, secure, and cost-effective data solutions on the Google Cloud Platform.

Translate complex business requirements into cloud-native data warehouses, data lakes, and streaming pipelines, while ensuring strict data governance, platform modernization, and optimization for AI/ML workloads.

Core Responsibilities

• Platform Architecture: Design and build end-to-end cloud-native data platforms (Data Lakes, Data Warehouses).
• Data Pipelines: Architect and optimize robust ETL/ELT pipelines for batch and real-time processing.
• Cloud Migration: Lead the transition and modernization of legacy on-premises data systems (e.g., Teradata, Oracle, Informatica) to Google Cloud Platform.
• Data Modeling: Translate business needs into logical, conceptual, and physical data models (e.g., star/snowflake schemas, Data Mesh concepts).
• Governance & Security: Implement enterprise-grade security frameworks, data masking, and metadata management.
  
  

Required Skills & Qualifications

• Google Cloud Platform Core Services: Deep, production-level expertise in BigQuery, Cloud Storage, Dataflow, Data Fusion, Dataproc, and Pub/Sub.
• Programming Languages: Proficiency in Python and SQL.
• DevOps & Orchestration: Experience with Infrastructure-as-Code (Terraform) and workflow orchestration (Cloud Composer/Apache Airflow).
• Experience Level: Typically requires 15 years of experience in data engineering or architecture, with at least 3–5 years focused specifically on Google Cloud Platform environments