Data Engineer
Bachelor’s degree in computer science, Engineering, Statistics, Mathematics, or related field. Master's degree preferred. Advanced English is mandatory 1+ years of experience as Data Engineer Cloud data storage is mandatory Strong understanding of data modeling, ETL processes, and data warehousing concepts Experience in SQL language, relational data modelling and sound knowledge of Database administration is mandatory Proficiency in Python related to Data Engineering for developing data pipelines, ETL (Extract, Transform, Load) processes, and automation scripts. Proficiency in Microsoft Excel Experience within integrating data management into business and data analytics is mandatory Experience working with cloud platform for deploying and managing scalable data infrastructure Experience working with technologies such as DBT, airflow, snowflake, Databricks among others is a plus Excellent Stakeholder Communication Familiarity with working with numerous large data sets Comfort in a fast-paced environment Strong analytical skills with the ability to collect, organize, analyses, and disseminate significant amounts of information with attention to detail and accuracy Excellent problem-solving skills Strong interpersonal and communication skills for cross-functional teams Proactive approach to continuous learning and skill development Experience in leading or collaborating with a team of data scientists and engineers in developing and delivering machine learning models that work in a production setting.. Data Infrastructure Development: Design, build, and maintain scalable data infrastructure on Cloud Platforms for data processing to support various data initiatives and analytics needs within the organization Data Pipeline Implementation: Design, develop and maintain scalable data pipelines to ingest, transform, and load data from various sources into cloud-based storage and analytics platforms using Python, and SQL Collaboration and Support: Collaborate with cross-functional teams to understand data requirements and provide technical support for data-related initiatives and projects. Helping translating business realities into data bases solution. Performance Optimization: Optimize data processing workflows and cloud resources for efficiency and cost-effectiveness. Implement data quality checks and monitoring to ensure the reliability and integrity of data pipelines. Build and optimize data warehouse solutions for efficient storage and retrieval of large volumes of structured and unstructured data. Data Governance and Security: Implement data governance policies and security controls to ensure compliance and protect sensitive information across cloud platforms environment.
Наблюдалась 2026-09-14, впервые 2026-08-17, источник — Get on Board (LATAM).