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Snowflake Data Architect

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About the Role

Candidates with 4-12 years of Snowflake Data Cloud experience are sought to lead scalable data solutions design and implementation.

The ideal candidate excels in Snowflake architecture, data warehousing, and serverless/cloud automation.

Key Responsibilities:

  • Design 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 expertise in Snowflake architecture (compute, storage, security, data sharing).
  • Use Snowflake native load utilities 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.
  • Drive meetings and translate business needs.

Qualifications:

  • Bachelor's/master's in computer science, IT, or related field.
  • 4-12 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.
  • Data governance, security, and compliance background.
  • Performance optimization and cost management skills.
  • Experience with Snowflake infrastructure management.
Skills and Qualifications

Candidates should have hands-on Python for data engineering/automation, knowledge of AI, LLMs, and Snowflake AI features, and experience with data lake frameworks and serverless technologies.

Familiarity with data modelling, Python, Pyspark, and warehousing best practices is a plus. Experience with MLOps, AI/ML pipelines, or deploying AI models is also desirable.

Preferred Qualifications

Snowflake or relevant cloud certifications are an asset.