I design, develop, and optimize Snowflake-based data architectures, including data modeling (Star/Snowflake schema), ELT pipelines, and performance tuning using Snowflake SQL, Tasks, Streams, Warehouses, and Zero-Copy Cloning. I have extensive experience implementing cost optimization, query tuning, workload isolation, and data governance within Snowflake to support enterprise-scale analytics. On the ingestion and orchestration side, I build end-to-end ELT pipelines using AWS S3, AWS Glue, Lambda, and Python/PySpark, integrating seamlessly with Snowflake for batch and near–real-time processing. I work closely with analytics, BI, and data science teams to deliver secure, reliable, and analytics-ready datasets. I bring strong expertise in SQL, Python, PySpark, Apache Spark, Hadoop, and NoSQL databases, along with best practices in cloud architecture, CI/CD, and data engineering standards.