• Design, Develop and Integrate ETL/ELT data pipelines for the necessary data from several sources for analysis and for Technology actions;• Build applications and products that make use of large volumes of data and generate outputs that allow actions that generate incremental value;• Deliver and implement core capabilities (frameworks, platform, development infrastructure, documentation, guidelines, and support) to speed up delivery in assuring quality, performance, and alignment to the technology blueprint and patterns;• Support stakeholders and functions in obtaining benefiting business value from the operational data;

• Read, analyze, and digest what a business wants to accomplish with its data, design the best possible ETL process, and use it todesign and create the data warehouse and all related extraction, transformation, and load data functions.• Automate functions applied to the data warehouse and integrate with other systems.• Data cleansing on data warehouse models that are not used in reports, stored procedures, jobs, and views.• Check Impact Analysis for any change maybe impact ETL jobs or Reports• Conduct thorough impact analysis for proposed changes to ETL processes or reports, ensuring continuity and performance stability.• Architect and implement a new data loader and backend for the Product Catalog Application, including comprehensive data warehouse design.• Lead the redesign and migration of all reports to the new loyalty platform (MASS - RED)• Develop and deploy new microservices and apis to support various business domains

• Build Data Warehousing with SQL Server to serve the Reporting Team in different Areas.• Build an operational data store (ODS) to serve Online Dashboards.• Management ETL Jobs using Python & SSIS• Build Integrate pipeline with ABB, Siemens, SharePoint Systems

• Apply market basket analysis using apriori algorithm using SSAS to find frequent item sets in transactions and identify association rules between these items.• Detect finger counter using hand tracking and OpenCV to integrate as a computer vision function.• Apply a sentiment analysis to e-market using NLP techniques (LSTM, BERT, and LINEAR SVC), to classify text as either positive or negative.• Built dashboards and investigated a variety of datasets to find problems, trends, and new opportunities.• Web scraping the climate of some cities in Spain using selenium and beautiful soup.