Snowflake Data Architect-Snowflake Data Modeling

Client Visa Sponsorship

Client is not sponsoring any VISA.

• Snowflake expertise:
  Warehouses, databases, roles, RBAC, SCIM, MFA.
• Data Engineering: ELT/ETL tools (dbt, Talend), orchestration (Airflow).
• Cloud Platforms: AWS, Azure, or Google Cloud Platform with Snowflake integration.
• Programming: SQL, Python; familiarity with ML frameworks.
• Security & Compliance:
  Data masking, encryption, audit processes.
• Strong experience with LLMs (OpenAI, Anthropic, Hugging Face, Lang Chain).
• Proficiency in Python and modern AI frameworks.
• Familiarity with vector databases, prompt engineering, and AI best practices.
• 5 years of product-focused engineering experience.
• Knowledge of cloud deployment and scaling AI systems.
• Strong SQL and Python skills.
• Hands‑on experience with dbt and Snowflake.
• Familiarity with cloud platforms (AWS).
• Knowledge of CI/CD, Dev Ops practices, and data orchestration tools (Airflow, Pref).
• Ability to create lineage graphs, documentation, and validation frameworks.

snowflake, Cortex AI, AWS, DBT

• Design and manage data pipelines using dbt, Airflow, and CI/CD frameworks.
• Implement Snowpipe for continuous ingestion, Streams & Tasks for real-time processing.
• Enable AI/ML integration:
  Support predictive analytics and generative AI use cases.
• Leverage Snowflake Cortex and Copilot for LLM-based applications.
• Ensure data governance, RBAC, and security compliance across Snowflake environments.
• Optimize performance and implement Time Travel, Zero Copy Cloning, and Secure Data Sharing.
• Build production‑ready AI applications and LLM‑powered features.
• Collaborate with AI Data teams to develop agentic AI workflows.
• Experiment with open‑source models and translate prototypes into production systems.
• Implement RAG pipelines, fine‑tuning, and observability for AI models.
• Design and deploy secure, scalable, and highly available architectures on AWS.
• Select appropriate AWS services for application design and deployment.
• Implement cost‑control strategies and disaster recovery plans.
• Collaborate with teams to integrate systems and ensure compliance.
• Develop Infrastructure as Code (IaC) using Terraform or Cloud Formation.
• Design, build, and maintain data pipelines using dbt for analytics and operational use cases.
• Implement standards for data quality, consistency, and reliability. Optimize query performance and manage compute costs.
• Collaborate with analysts and stakeholders to understand data requirements.
• Build automation into workflows and ensure compliance with governance policies.