Snowflake Architect

Key responsibilities

• Design and implement Snowflake-based data architecture and data models
• Build and optimise data pipelines (ETL/ELT) using Python and advanced SQL
• Orchestrate workflows with dbt and Airflow or an equivalent tool
• Deploy and manage data solutions on AWS, Azure or GCP
• Set up CI/CD and version control using Git
• Enforce data quality, governance and security standards
• Build GenAI-ready data architecture, including RAG and AI agents that interact securely with enterprise data

Must-have skills

• Python
• Advanced SQL
• Data pipelines / ETL / ELT
• Snowflake
• Data modeling
• dbt
• Airflow or equivalent
• Cloud: AWS, Azure or GCP
• Git and CI/CD
• Data quality and governance

Good to have

• Spark / PySpark
• Kafka / streaming
• Iceberg / Delta Lake
• Docker / Kubernetes
• Data observability
• Semantic layer
• Cost and performance optimisation

GenAI exposure

• RAG
• AI agents
• MCP
• GenAI-ready data architecture
• Building agents that securely interact with enterprise data