Creative and Experienced Data Engineer with over 4 years of extensive hands-on on Modern Data Stacklike Snowflake, AWS, DBT, Python, ETL, Streamlit etc. for high-volume companies. Passionatein problem solving in Data Platform.Working as a Data Engineer in a Data Warehousing (Snowflake) project for an American manufacturing giant. Responsible for gathering business requirements, documenting, and implementing them in the Logical/Physical data model.Utilizing Snowflake features like Snowpipe for real-time data ingestion, Time Travel for historical data recovery, and Streams & Tasks for building event-driven data pipelines. Responsible for maintaining data quality using clustering and partitioning strategies for performance optimization.Implementing various Data Modelling and data warehousing techniques using tools like Snowflake, DBT, and Python Scripting. Leveraging dbt features like model versioning, incremental models for efficient data updates, and snapshots for tracking slowly changing dimensions. Responsible for handling queries from Build/Testing teams and Business users.Designing and implementing end-to-end data pipelines using dbt models, ensuring efficient data extraction, transformation, and loading (ETL) processes. Automating workflows with dbt run, dbt tests, and dbt seeds to validate and test data pipelines, with minimal manual intervention.Performing enhancements on existing Data Pipelines for efficient data flow, utilizing Streams to track changes in tables and ensure seamless data updates.Responsible for Pre and Post Migration Analysis, presenting outcomes to the business using Snowflake Time Travel for validating historical data, and dbt docs for clear data lineage documentation.Managing the Data Platform Team to continuously improve the overall data platform. Working on optimizing query execution and data processing using dbt materializations (e.g., views, tables, and incremental loads) and Snowflake automatic clustering for efficient data organization.