Snowflake Architect is responsible for designing, implementing, and optimizing data solutions using Snowflake Cloud Data Platform. They ensure scalability, security, and high performance in data warehousing, analytics, and cloud data solutions. Role & responsibilities 1. Architecture & Design Design end-to-end data solutions using Snowflake Cloud Data Platform. Define data architecture strategy, ensuring scalability and security. Establish best practices for Snowflake implementation, including data modeling, schema design, and query optimization. Design data lakes, data marts, and enterprise data warehouses (EDW) in Snowflake. 2. Data Engineering & Development Oversee ETL/ELT pipelines using Snowflake Snowpipe, Streams, Tasks, and Stored Procedures. Ensure efficient data ingestion, transformation, and storage using SQL, Python, or Scala. Implement data partitioning, clustering, and performance tuning for optimized query execution. 3. Security & Compliance Implement role-based access control (RBAC) and data governance policies. Ensure encryption, auditing, and data masking for security compliance. Define multi-cloud strategies (AWS, Azure, GCP) for Snowflake deployments. 4. Performance Optimization Optimize query performance and warehouse compute resources to reduce costs. Implement Materialized Views, Query Acceleration, and Caching to improve performance. Monitor Snowflake usage, cost management, and auto-scaling capabilities. 5. Integration & Automation Integrate Snowflake with BI tools (Tableau, Power BI, Looker), data lakes (S3, Azure Blob, GCS). Automate data workflows and pipeline orchestration using Airflow, dbt, or Snowflake Tasks. Implement CI/CD pipelines for data model deployments and schema changes. 6. Stakeholder Collaboration & Leadership Work closely with business analysts, data scientists, and IT teams to define requirements. Act as a technical advisor for Snowflake-related decisions and best practices. Provide mentorship and training to data engineers and analysts on Snowflake architecture. Key Skills Required: Snowflake Data Warehouse (Warehouses, Secure Data Sharing, Multi-Cluster Architecture) SQL, Python, Scala (for data processing and scripting) ETL/ELT & Data Pipelines (Informatica, Talend, dbt, Airflow) Cloud Services (AWS, Azure, GCP integration) Performance Tuning (Query Optimization, Snowflake Caching) Security & Governance (RBAC, PII Data Masking, Compliance) BI Tools Integration (Tableau, Power BI, Looker)
