Data Engineer

• Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Systems Analysis and Development, or similar; • Advanced English; • Use data pipeline frameworks and libraries to automate data processing tasks and optimize workflows. • Follow best practices for developing data pipelines, including version control, testing, and thorough documentation. • Understand and utilize cloud computing platforms and services offered by providers such as AWS, Azure, and Google Cloud. • Develop data pipelines using orchestration frameworks (e.g., Apache Airflow, Luigi, Mage, Databricks Workflows), integrating with PySpark and/or Scala as needed. • Understand and apply software design principles to data engineering projects. • Optimize PySpark and SQL query performance, considering data volume, query complexity, and system resources. • Use data tools for ingestion, transformation, analysis, and visualization. • Logical reasoning and analytical skills; • Meeting deadlines and delivering quality work; • Effective and transparent communication with other teams and coworkers; • Communication and interpersonal skills to present and discuss cases with other involved areas; • Autonomy in performing tasks; • Develop and maintain APIs for data exchange between applications. • Experience with cloud computing platforms (AWS, Azure, Google Cloud) and their services. • Use automation frameworks and tools such as Azure DevOps, Terraform, and GitHub Actions.