Eric De Carvalho Email & Phone Number

I am a Data Engineering Analyst with a degree in Electrical Engineering from the Federal University of Espírito Santo (UFES) and technical training in Industrial Automation from the Federal Institute of Espírito Santo (Ifes). My career is characterized by a consistent and comprehensive focus on data engineering, with solid experience in data extraction, transformation, and analysis of large-scale datasets. I am dedicated to designing sophisticated solutions for data integration and processing that ensure the accuracy, integrity, and quality required by critical applications. My approach, driven by innovation and continuous improvement, leverages data as a strategic foundation for scalable architectures, the development of efficient pipelines, and evidence-based decision-making.Currently, I serve as a Data Engineering Analyst at EloGroup, where I act in projects involving the design and implementation of data pipelines and models using an advanced technological stack that includes Python, SQL, PySpark, Databricks, and Azure solutions such as Azure Data Factory and Azure Data Lake Storage. My responsibilities encompass large-scale data integration and processing, generating high-value insights that enhance operational processes and improve efficiency across all stages of the data lifecycle.Committed to continuous skill enhancement and adopting industry best practices, I participated in the Data Engineering course on the ADA platform, sponsored by Santander, where I deepened my knowledge in data architecture, pipeline design, data warehouses/data lakes, and data governance. My experience also extends to academic research, including involvement in a Scientific Initiation project focused on Intelligent Video Monitoring Applied to Public Safety (UFES/IFES) and my work as an extension student on the Solares Project, developing solutions for telemetry and energy management.My competencies include rapid learning capability, well-honed interpersonal skills, and a collaborative approach. I am prepared to tackle complex challenges and contribute substantial value to multidisciplinary projects and teams in the field of data engineering.