Snowflake Data Architect

• Define star schema patterns, Snowflake object hierarchies, and modelling conventions that serve as the Group-wide standard for all data products.
• Design and implement secure, high-throughput data pipelines connecting AWS S3 and Azure APIs through Snowflake, ensuring data integrity, lineage tracking, and end-to-end auditability.
• Own the full security model for the Snowflake platform, including RBAC policy design, dynamic data masking, row-level security, and comprehensive audit logging across all environments.
• Monitor Snowflake credit consumption, identify and remediate high-cost query anti-patterns, and implement warehouse scheduling strategies to reduce operational data spend.
• Architect data stores purpose-built for LLM consumption, including vector databases, embedding pipelines, and RAG-compatible data structures.
• Partner with Business Analysts to define and document Data Contracts between systems, creating clear interfaces between producers and consumers across the data platform.

Technologies:

• AI
• AWS
• Architect
• Azure
• Cloud
• Data Vault
• Data Warehouse
• IAM
• LLM
• Python
• RBAC
• SQL
• Security
• Snowflake
• dbt

• Solid experience in Data Engineering or Data Architecture, with at least 4 years specialising in Snowflake platform design and governance.
• Strong mastery of Data Warehouse design methodologies, including Inmon, Kimball, and Data Vault 2.0, with the judgment to apply the right pattern for each use case.
• Expert-level SQL and Python skills.
• Hands-on experience with dbt or equivalent transformation frameworks.
• Solid understanding of AWS IAM, S3 data lake patterns, and PrivateLink for cross-cloud data connectivity.
• Practical experience architecting data infrastructure for AI/ML consumption, including vector databases, embedding stores, and RAG pipeline integration.
• Strong interpersonal skills with the ability to translate complex data architecture into clear language for Business Analysts and non-technical stakeholders.