- Contributed to the migration of data from an on-premise Hadoop environment to AWS Cloud, automating the ingestion process for 50000+ tables into a new data lake and data mesh architecture, enhancing data accessibility and scalability.- Contributed to the development of an internal Python library that accelerates the creation of Spark-based ETL jobs in AWS. This library is used by 1000+ daily ETL jobs, offering modules for: unit testing, connectors, function wrappers, data cleaning, data quality and metrics. Result: Improved the company’s ETL job creation time by 42%.- Contributed to designing the ETL architecture used by the data engineers to ingest data from multiple sources, including on-premise systems, JDBC, RDS, and Mainframe environments, ensuring seamless integration into the data mesh.

- Automated the extraction and cleaning of data from six different sources using Python to create a report identifying POS with the highest sales opportunities- Developed a heatmap report identifying the cities where the competition was gaining market share and automated recommendations for actions to take at each POS.- Developed dashboards to visualize results and performance indicators for the field team and management.

- Developed an ETL process using VBA and Python to extract data from SAP and deliver automatic reports to the sales team.- Developed performance reports, sales dashboards and tracked commercial indicators (Sales Force, Sales Funnel, KPI Dashboards, and Route Planner).- Pricing and margin analysis for large-scale projects (infrastructure and real estate) in the Northeast region.