Next (Digital Bank) Customer - Analytics Support and Data Ingestion Team-Responsible for ensuring data and environment integrity and executing data ingestion processes.-Utilized Data Factory pipelines for ingesting data from Hive and Oracle sources.-Developed comprehensive and incremental data ingestion processes in Databricks using ETL techniques to transform data into suitable formats for analysis.-Created tables and applied transformations in the bronze and silver layers, ensuring anonymization and compliance with data security standards.-Maintained data pipelines and code in Databricks to ensure stability and quality of processed data.OdontoPrev Customer-Integrated the team responsible for migrating data from the on-premise environment to the Azure cloud environment.-Utilized Azure Integration Services to transfer data from the on-premise environment to Azure Synapse.-Developed SQL procedures for specific tables in various business areas.-Provided support for data migration to ensure data integrity and quality.-Analyzed and identified problems, seeking effective solutions for the project.Bradesco Seguros Customer-Currently working as part of the best practices team for the data migration project from on-premise to the Azure cloud environment at Bradesco Seguros.-Developed dynamic pipelines for data ingestion in Azure Data Lake Gen2 and Databricks.-Defined data ingestion strategies.-Provided support for the migration project.Technologies utilized:Azure cloud environment for overall project execution and support.

I worked in the front-end development of the new Santander ATM using Typescript and Angular framework.I worked in the front-end development of Open Banking Santander using Typescript and Angular framework.Technologies Used:typescriptAngularGitJenkinsConcepts Covered:Scrum MethodologyRXJS Reactive ProgrammingPOODevOp

Development of scripts for data mining via WebScrapping.Development of a robot for automating SQL scripts.I worked on the development of the Cloud data platform, building automated pipelines. Performing the ETL process integrating different data sources, processing and loading in the Data Warehouse.Technologies used:-Python-SQL-Google Cloud Platform-Git- Talend Data Integration-Office packConcepts Covered:-Data Mining-Scrum Methodology-Big data-Data Engineering-ETL

Analysis, data treatment and creation of scripts through the SQL SERVER database tool. Application creation and validationQlikview. Analysis for data correction and file processing in the ETL tool. Importing and exporting data to the database. Load programming in BI and data analysis in Qlikview. Generation of data evidence as well as identification of errors in dashboard indicators. Documentation of SETUPs. Responsible for ensuring data quality in ETL, BI, dashboard before sending it to the client. Using SQL Server 2014 tools, Integration Service, Nprint and Qlikview