Job Title

- Define and own the end-to-end architecture of data platforms built on Snowflake, including ingestion, transformation, storage, and consumption layers. - Design and implement data lakehouse architectures using Snowflake’s native features such as Streams, Tasks, Materialized Views, and External Tables. - Establish best practices for data governance, security, and access control using Role-Based Access Control (RBAC), Secure Views, and Row-Level Security. - Architect scalable ETL/ELT pipelines using Snowflake, DBT, and Python, integrating with orchestration tools like Airflow etx. - Lead integration of Snowflake with enterprise systems such as data catalogs, data quality frameworks, monitoring tools, and BI platforms. - Working knowledge of AI integrations with Snowflake, including Snowflake Cortex and LLM-powered analytics, with experience in enabling intelligent data applications. - Guide teams in implementing CI/CD pipelines for Snowflake deployments using tools like GitHub Actions, Azure DevOps, or GitLab CI. - Monitor and optimize Snowflake performance using Query Profile, Resource Monitors, Clustering Keys, and Auto-Suspend/Resume features. - Collaborate with data analysts, engineers, and business stakeholders to ensure platform reliability and data accessibility. - Conduct architectural reviews, code audits, and mentoring sessions to ensure adherence to standards and scalability.