Snowflake Development:Design, build, and optimize ETL pipelines within and outside of Snowflake.Develop scripts using languages like Python, Unix, or other relevant technologies for data loading, extraction, and transformation.Create and maintain views, stored procedures, and other database objects in Snowflake.Optimize query performance and troubleshoot data-related issues.Databricks Integration:Collaborate with data scientists and analysts to integrate Snowflake with Databricks.Build and maintain highly scalable data pipelines using Databricks, Azure, AWS, or other cloud platforms.Design and implement ETL/ELT data pipelines to extract, process, and transform data from various sources.Work on data insights, machine learning models, and fraud detection within the Databricks environment.Data Quality and Security:Implement extensive data quality checks to ensure high-quality data.Define and enforce data security measures within both Snowflake and Databricks.Monitor and manage access control for data assets.Collaboration and Communication:Collaborate with business leaders to understand organizational goals and align data engineering efforts.Communicate data trends, insights, and recommendations to business executives.