At REPAY - Realtime Electronic Payments, I apply my MS in Data Analytics and Machine Learning to design and implement data warehouse solutions in AWS, where I ingest, transform, and validate data from 13 distinct acquisitions using Python, Pydeeque, and Great Expectations. I also monitor and orchestrate data and ML pipelines using Airflow and Databricks, and deploy Kafka on Kubernetes for containerization and AWS Kinesis for automation. My previous roles as a Software Engineer at Ford Motors and an Analytical Consultant at Wells Fargo enabled me to develop and support complex reporting and ETL solutions using SQL, SSRS, .NET/C#, and Python, and to perform data mining and analysis using Tableau, SAS, and Power BI. I automated and optimized data processing and report generation, reducing time and errors by up to 75%. I also created data validation using SAS Financial Management and documented evidence. I am a versatile, detail-oriented, and collaborative learner who can translate business requirements into technology and action. I have excellent problem-solving, communication, and analytical skills, and I use various visualization tools such as Sisense, Alteryx, and Qlikview to present and enhance the data insights for business change. I take ownership of the project's end-to-end delivery and work cross teams to realize optimal solutions.