I led the technical team in migrating applications with 10,000 lines of code to the Google Cloud Platform. This involved reengineering the code and understanding the business logic. We successfully used Python, Dataproc, Big Query, Terraform, Tekton, and Astronomer during the migration.Managed Google projects while ensuring compliance with company policies regarding creating Google-Managed Service Accounts and Vault Keys, ensuring role-based access controls.Governed the team and ensured enabling DEVSECOPS tools. Instituted applying fixes for the observations by the DEVSECOPS tools.Achieved committed targets of 3 Major Google Cloud Migration deployments to enable partner business support.Developed and executed a comprehensive roadmap for product development, delivering incremental value with each iteration through frequent deployments.I led the deployment of five data products that improved business efficiency by interconnecting all the siloed data for analytical consumption. Achieved all the commitments, including creating the cloud project, launching SaaS products, developing a robust framework, setting up the pipeline and CI/CD processes, preparing for Astronomer deployment, creating GitHub repositories, and establishing Big Query datasets. This solid foundation positions us for continued success and growth.This solid foundation positions us for continued success and growth.

Developed an impactful Customer 360 data model to elevate customer data assets, automatically driving more effective Next Best Offer campaigns across every product line in a real-time fashion.Designed ETL applications for Customer 360 source datasets, including product and customer segmentation datasets.Devised integration of all the model scores, building strategies to find a way to tie up scores from multiple ML Models, Implemented using Python and Apache Spark tools.Architected the R-Shiny Dashboard for Action Management framework, which was utilized to insert and update the new offers and actions that help automatically extend the specific campaign offers for the targeted customers.Reduced churn through Pay Monthly campaigns by targeting customers likely to accept the offer. This approach utilized supervised machine learning techniques focused on customer usage behavior. The tools employed in this process included the Azure ML products in the cloud.

Architected, Designed, and Deployed Acquisition-Base-Churn Data Models, enabling telecom post-paid & pre-paid product line-level reporting data using IBM DB2 Telecom Data Warehouse Industry Reference Models.I integrated all the separate sources of information and developed strategies to establish a single source of truth for each telecom product line. This initiative enhanced the market value data for our products and reduced errors in determining campaign costs and customer lifetime value.Successfully reduced churn through targeted broadband campaigns aimed at customers likely to accept the offer. This was achieved using supervised machine learning techniques focused on customer needs and usage behaviors. Increased revenue by selling wireless services to targeted customers likely to accept the offer using machine learning techniques.

Designed and Built NO SQL Data Model solutions for a US Retail Client using Google Big Table.Architected and Designed pipelines for ETL and data integration tasks using Talend Open Studio.Deployed Data Integration Pipelines using Pentaho tools, integrated Apache Hadoop data with Amazon S3 files, and developed data marts for reporting for a US Banking client.

Designed analytical applications for the automotive firm using Teradata ETL tools (MLOAD, FASTLOAD, BTEQ, TPUMP).Architected IBM Datastage ETL Jobs (Change Data Capture) for Customer Master Data Handling.Designed Data Profiles and Quality tests for Informatica ETL Jobs using Informatica Power Center.Engaged with multiple teams to architect and integrate Customer Marts using IBM MDM Data Model for customer data Domain.Catapulted Consumer Data Marts, applying Customer Data Domain skills.Designed and Deployed IBM UDB DB2 Stored Procedures for Data Marts.Expertise in working with IBM Data Studio tool for all the Query Optimization and serving ad-hoc data requests.

Spearheaded a team of talented individuals to develop applications using IBM Mainframe technologies such as DB2, CICS, PACBASE, JCL, IMS, VSAM, Endeavor, and COBOL for automotive systems.Mentored over 100+ team members in the PACBASE code generation tool.Formulated delivery date calculation logic for the shipping of vehicles for an automotive firm.

Expertise in EDI codes enabled them to ascertain logistics communication with customers regarding delivery.Achieved seamless integration of various systems, enhancing efficiency and productivity in the Operations & Support, achieving Operations Excellence.

Designed applications for a manufacturing firm using IBM Mainframe stacks such as DB2, JCL, and Cobol.Deployed Electronic Data Interchange Communication Codes for Logistics handling on shipping products to customers.Accelerated batch processing efficiency and performance through continuous tuning & optimization on DB2 SQL Queries for a US-based financial services firm.