Data Engineer

Responsibilities

• Design and implement unified data warehouses and data lakes to support analytics and AI workloads
• Define data architecture strategies, including storage layers, access patterns, and scalability
• Build and maintain ETL/ELT pipelines using Databricks and Azure Data Factory
• Integrate data from multiple enterprise source systems such as ERP and CRM platforms
• Establish data quality standards, validation rules, and anomaly detection processes
• Implement data cataloging, lineage tracking, and documentation for transparency
• Collaborate with data scientists and BI analysts to ensure data products meet requirements
• Optimize query performance, pipeline efficiency, and infrastructure costs

Requirements

• Minimum 5 years of professional experience in data engineering or a related field
• Expert-level proficiency in SQL, including complex query design and performance tuning
• Hands-on experience with Databricks for large-scale data processing
• Proven experience designing enterprise-scale data warehouse or data lake solutions
• Strong understanding of ETL/ELT design patterns and data modeling methodologies
• Professional-level proficiency in Spanish
• Working proficiency in English

About the Company

GEA is one of the world’s largest systems suppliers for the food, beverage, and pharmaceutical sectors. The international technology group focuses on providing advanced process technology, machinery, and components to enhance the sustainability and efficiency of production processes globally.