Google Cloud Platform Data Architect
Role details
Job location
Tech stack
Job description
Platform Architecture: Design and implement end-to-end data solutions, including modern data lakes, data warehouses, and batch/streaming data pipelines.
Cloud Modernization: Lead the migration of on-premises or legacy data warehouses (e.g., Teradata, Oracle, Informatica) to Google Cloud Platform-native architectures.
Data Governance & Security: Implement strict data security frameworks, data masking, and metadata management strategies to ensure compliance and privacy.
Collaboration: Partner with data engineers, data scientists, and business analysts to optimize analytical workloads and support AI/ML initiatives.
Best Practices: Establish CI/CD pipelines, automated deployments, and cost-optimization measures across the Google Cloud Platform ecosystem.
Requirements
Experience: 8+ years of hands-on experience in data engineering or architecture, with at least 4 5 years focused on Google Cloud Platform-native environments.
Google Cloud Platform Core Services: Deep knowledge of BigQuery (data warehousing), Cloud Data Fusion/Dataflow (ETL/ELT), Dataproc (Spark/Hadoop), and Pub/Sub (event streaming).
Programming & Scripting: Strong proficiency in Python, SQL, and shell scripting.
Orchestration & DevOps: Experience with workflow orchestration tools (e.g., Cloud Composer / Apache Airflow) and infrastructure-as-code (Terraform).
Data Modeling: Solid understanding of dimensional modeling, star/snowflake schemas, and data mesh/data fabric concepts.