Developed and maintained an enterprise data lake in Azure, organizing data from over 100 stores nationwide, improving data accessibility and reliability.Automated ETL processes with Azure Data Factory, which facilitated real-time data integration and analysis, improving operational efficiency and decision-making speed.Implemented a scalable data warehouse solution that supported high concurrency and volume, optimizing query performance significantly. This initiative allowed us to achieve near real-time analytics, enhancing our inventory management and customer service.Automated the transformation of raw data into actionable insights within our Snowflake environment. This tool allowed me to streamline the workflow from data ingestion to insight generation, ensuring data quality and consistency across our analytics platform.

Developed a real-time fraud detection system using AWS Kinesis and Machine Learning models to analyze payroll transactions, significantly reducing fraudulent activities.Designed and optimized ETL pipelines for ADP's HR analytics platform using AWS Glue, improving data ingestion from diverse sources including HR systems, time tracking, and benefits management.Automated data transformation processes that enriched payroll data with tax information, enhancing the accuracy of tax filings for clients.Implemented CI/CD pipelines using AWS CodeBuild and CodePipeline for seamless deployment of ETL jobs and data models, reducing deployment time by over 60% and ensuring higher code quality.Utilized Terraform to automate the provisioning of AWS resources for a scalable HR data analytics platform, ensuring compliance with security and governance policies.Created reusable Terraform modules for rapid deployment of development and testing environments, improving the productivity of the data engineering team.Applied deep domain knowledge in payroll and HR services to design data models that accurately represent complex business rules, compliance requirements, and client-specific configurations.