Data Engineer

Responsibilities

• Implement and manage data quality processes, ensuring accuracy and consistency through automated validations and continuous monitoring
• Define and apply data governance standards aligned with global guidelines, including metadata, ownership, and stewardship
• Develop, optimize, and maintain scalable data pipelines using tools such as Azure Data Factory and Databricks
• Ensure continuous ingestion, transformation, and availability of data for analytics, reporting, and machine learning initiatives
• Standardize and harmonize data structures and definitions across different LATAM markets
• Maintain and evolve data documentation, including definitions, data lineage, and usage policies
• Implement and monitor FinOps practices within Databricks to ensure cost efficiency and control

Requirements

• Degree in Engineering, Computer Science, Information Systems, Data Science, or a related field
• Solid experience in data engineering, specifically building and maintaining end-to-end pipelines
• Proficiency in Python (especially PySpark) and SQL
• Experience with Databricks and Data Lake architectures (raw, bronze, silver, and gold layers)
• Practical experience with Data Quality and data governance practices
• Intermediate proficiency in both English and Spanish

Preferred Qualifications

• Experience applying FinOps to Databricks environments
• Knowledge of automation tools such as Power Automate
• Experience working in regional or multi-country environments, preferably within FMCG or B2B sectors

About the Company

Unilever is a global leader dedicated to equity, inclusion, and diversity. We aim to drive business results while creating a better future for our employees, consumers, and communities. At Unilever, we believe in empowering our people to bring their "whole selves" to work and making a meaningful impact on the planet.