Snowflake Data Architect

We are seeking a highly experienced Snowflake Data Architect with deep expertise in dbt, data modeling, and modern data platforms. This role will lead the design and implementation of scalable, secure, and cost-efficient data architectures, while driving innovation using AI/GenAI capabilities (Cortex AI). The ideal candidate will serve as a technical leader, guiding data engineering teams and aligning data solutions with business objectives., <>Architecture & Design

• Design and maintain end-to-end data architecture using Snowflake as the cloud data warehouse
• Define and enforce data modeling standards (Dimensional, Data Vault, Hybrid, Semantic Layers)
• Architect scalable and cost-efficient Snowflake environments (databases, schemas, warehouses)
• Establish strategies for data ingestion, transformation, and consumption
• Review and approve technical designs and data pipelines, * Lead dbt implementation using Datacoves
• Define dbt project standards (naming conventions, folder structures)
• Develop:

• dbt models, macros, snapshots, and seeds

• Implement data quality tests (freshness, generic, custom)
• Enable data lineage and documentation via dbt docs
• Establish CI/CD pipelines for dbt deployments, * Optimize Snowflake performance using:

• Clustering & micro-partitioning
• Query optimization
• Warehouse sizing and scaling

• Monitor and manage Snowflake cost efficiency
• Implement ELT best practices
• Collaborate with data ingestion tools and pipelines, * Act as a technical advisor to data engineers and analytics teams
• Mentor junior team members
• Translate business requirements into scalable technical solutions
• Collaborate with stakeholders to define KPIs and semantic layers
• Contribute to data platform roadmap and architecture strategy

• 10+ years of overall IT experience
• 8+ years of experience in data engineering / analytics engineering
• 8+ years of hands-on Snowflake architecture experience
• 6+ years of experience with dbt (Core or Cloud)
• Strong expertise in SQL (advanced transformations & performance tuning)
• Deep understanding of ELT architectures
• Experience with cloud platforms (AWS / Azure / Google Cloud Platform)
• Proficiency with Git-based version control and CI/CD pipelines
• Strong experience in data modeling methodologies, * Snowflake
• dbt (Data Build Tool)
• Python
• AI / GenAI (Cortex AI)
• SQL
• Cloud Platforms (AWS / Azure / Google Cloud Platform), * Strong communication and stakeholder management skills
• Experience in building enterprise-scale data platforms
• Exposure to modern data stack tools and frameworks