Working as Python Developer for CarmaxWorked as Machine Learning Engineer for Netspends• Building an end-to-end ML pipeline from Data Extraction to Model Deployment for targeting the reduction of IVR calls to agents from customersWorked as Data Engineer for the Amazon Ring• Developed ETL pipelines for different Data Metrics for Home Security devices involving AWS S3, Redshift and IAM roles and policies• Build an end-to-end Apache Airflow pipeline in Python involving multiple DAGs for web scraping, data transformation, and data imports to S3 and Redshift with cross-IAM roles and policies to load the data in Redshift for the Sales team• Apache Airflow DAGs used AWS SSM-managed EC2 instances to run the python scripts to do above mentioned tasks Worked as Data Engineer for Gartner• Developed and migrated 30+ ETL pipelines from on-premise Informatica to Azure Data Factory• Developed generic ETL pipelines in T-SQL scripts to optimize the performance and reduce cost• Worked on different sources and targets while building parameterized ADF pipelines and functionalities of triggering email notifications and shell scripts on job status

Developed Project "Impact Analysis Engine for Microservices"• Developed API in Python for extracting the dependency graph for Microservices Architecture based upon the calls between Microservices..• These dependency graphs were helpful in finding the weightage of a particular service in MSA which in turn will find the severity of bug in MSA.• Used different python modules such as networkx, graphviz, plotly, pandas, regex Upset, etc.• The project also reduced the latency for component automation as QA is only needed for dependent services.