As a Senior Data Client Ops Analyst, I led a development team focused on building and optimizing data pipelines across both Azure and AWS. We utilized databases and functions to run Python and SQL scripts, significantly enhancing data quality and optimizing financial operations within business intelligence frameworks. Our efforts prioritized automation and refinement of data flows to ensure seamless platform migrations, supported by robust QA processes using pandas and numpy.We developed microservices with AWS Lambda , azure functions and Power Automate, built Azure PostgreSQL databases with source functions, and leveraged data lake capabilities for both S3 and Azure Blobs. Additionally, we created dynamic dashboards using Python and Power BI, providing advanced insights into media indicators for decision-making. Our architecture utilized AWS Lambda for serverless data processing, S3 for efficient storage, and Redshift for managing large-scale data warehouses, all of which contributed to a resilient and scalable data infrastructure. Power Automate further streamlined workflows and automated repetitive tasks.We also used Alteryx to automate complex data pipelines, which significantly boosted our forecasting and analytics capabilities. These integrations drove advanced financial strategies and operational efficiency across LATAM and India, fostering a high-quality, data-driven ecosystem that played a key role in driving business growth.

I developed and implemented information systems for automated data collection and maintenance using Power BI and Python, focusing on building applications for QA testing and process automation. I maintained high standards of data quality while engineering and managing big data reporting and visualization tools across LATAM. As a leader in business intelligence, I spearheaded development initiatives for process automation and data reporting teams.

Reporting and data analysis.

Data Quality and Auditing for The RealReal Client services. •Nps Dashboard creation and reporting in Power BI and Excel. •Contact center operation indicators•Headcounts Data Warehousing and Quality•Customer service interaction data reporting