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