Data Scientist

Engaged as a Junior Data Engineer with a focus on preventive measures at Banco Itaú, working on various aspects of data engineering and analytics. Assisted in the development and optimization of ETL/ELT data pipelines within both legacy systems and cloud environments. Contributed to the implementation of quality assurance measures to promote data accuracy and process efficiency. Utilized tools such as Apache Hadoop, Python, and SQL to support data processing tasks. Provided support for preventive processes, ensuring smooth data flow and enhancing analytical capabilities. Collaborated with team members to gather requirements and deliver data-driven insights.

Focused on analytics engineering and data engineering tasks, with a strong emphasis on constructing data pipelines and implementing quality assurance processes. Constructed data pipelines using ETL/ELT methodologies for both legacy systems and cloud environments, particularly AWS. Developed quality assurance protocols and preventive triggers to enhance data integrity. Provided both proactive and reactive support for preventive processes within the organization. Utilized Apache Hadoop technologies, including Hive and Impala, along with Python, PySpark, SQL, and AWS tools such as Glue, Athena, and S3.

Focused on data organization and analysis to support monitoring and reporting functions. Structured and validated data for reporting and closures, enhancing accuracy and efficiency. Analyzed data to understand business scenarios, contributing to informed decision-making. Monitored key performance indicators for the department to track progress and outcomes. Assisted in developing reports, dashboards, and performance presentations to communicate findings effectively. Utilized Power BI, SAS, and Excel for data analysis and visualization, improving data accessibility.

Focused on delivering data analysis and business intelligence solutions for cloud service consumption. Conducted thorough analysis to provide actionable insights regarding client cloud service usage. Designed and generated reports, dashboards, and presentations to communicate findings effectively. Utilized a range of tools including Power BI, Python, and Azure Data Factory to enhance data processing capabilities. Employed MySQL, Excel, SQL, and Azure Data Studio for data manipulation and visualization tasks.