Snowflake Architect Data Warehousing

Role Overview

Looking for an IT Professional with 9-14 years of hands-on Snowflake Data Cloud experience to lead the design, implementation, and optimization of scalable data solutions. The ideal candidate excels in Snowflake architecture, data warehousing, data lakes, serverless/cloud automation, and AI/LLM concepts.

Key Responsibilities

• Architect and deliver end-to-end data solutions on Snowflake.
• Demonstrate deep understanding of data warehousing concepts and work with structured, semi-structured, and unstructured data.
• Apply deep expertise in Snowflake architecture (compute, storage, security, data sharing).
• Use Snowflake native load utilities (e.g., Snowpipe, COPY INTO) for data ingestion and transformation.
• Develop and manage API-based integrations and automation.
• Lead data governance, quality, security, and compliance efforts.
• Optimize performance and manage costs.
• Oversee Snowflake infrastructure provisioning, scaling, and monitoring.
• Act as primary stakeholder contact; drive meetings and translate business needs.
• Foster innovation in data architecture, analytics, and AI-driven solutions.
• Collaborate with cross-functional teams.
• Stay current on Snowflake advancements, especially AI features like Cortex.
• Proactively perform POCs for new Snowflake features & drive adoptions.
• Leverage data lake frameworks & serverless technologies
  
  

• Bachelor’s/master’s in computer science, IT, or related field.
• 8+ years of Snowflake Data Cloud experience.
• Deep understanding of Snowflake architecture and ecosystem.
• Strong grasp of data warehousing concepts and diverse data structures.
• Expertise in Snowflake native load utilities.
• API integration and automation experience.
• Data governance, security, and compliance background.
• Performance optimization and cost management skills.
• Experience with Snowflake infrastructure management.
• Excellent communication and stakeholder management.
• Innovative, AI-driven mindset.
• Hands-on Python for data engineering/automation.
• Knowledge of AI, LLMs, and Snowflake AI features (e.g., Cortex).
• Experience with data lake frameworks and serverless technologies.