Working as a Data Engineer in a Data Warehousing (Snowflake) project for aTelecom 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, TimeTravel for historical data recovery, and Streams & Tasks for building event-driven data pipelines. Responsible for maintaining data quality using clusteringand partitioning strategies for performance optimization.• Implementing various Data Modelling and data warehousing techniquesusing tools like Snowflake, DBT, and Python Scripting. Leveraging dbtfeatures like model versioning, incremental models for efficient dataupdates, and snapshots for tracking slowly changing dimensions. Responsiblefor 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 tovalidate 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 thebusiness using Snowflake Time Travel.