Description
DATA ENGINEER
Data Engineer - Data Analysis Expert
Mexico City | Mex
Hybrid
Role Overview
We are seeking a Data Engineer to design, build, and optimize scalable data pipelines and models that power analytics and business insights. You’ll work across modern data platforms and tools—such as dbt, Snowflake, Informatica, and Airflow—to ensure reliable, high-quality data for decision-making. This role is ideal for an engineer who enjoys problem-solving, collaboration, and continuous learning in a fast-paced, data-driven environment.
Key Responsibilities
Design, build, and maintain automated ETL/ELT pipelines using tools like dbt, Snowflake, Informatica, and Airflow.
Develop and optimize data models to support analytics, reporting, and machine learning use cases.
Integrate data from multiple systems to create unified, high-quality datasets.
Ensure data accuracy, completeness, and consistency through validation and monitoring.
Collaborate with data analysts, product managers, and business teams to translate requirements into efficient data solutions.
Support data governance and quality initiatives, ensuring compliance with standards and best practices.
Contribute to the continuous improvement of data engineering processes, tools, and documentation.
Troubleshoot and resolve issues in data pipelines, optimizing for performance and scalability.
Stay current with emerging data technologies and engineering best practices.
Desired Skills & Experience
5–7 years of hands-on experience in data engineering or data development.
Strong proficiency in SQL and working knowledge of Python or another scripting language.
Experience with dbt for data transformation and Snowflake for cloud data warehousing.
Strong experience in Data Analytics and Data Curation.
Practical understanding of Informatica and Apache Airflow for data integration and orchestration.
Solid grasp of data modeling techniques (dimensional, star/snowflake schemas).
Familiarity with CI/CD workflows, Git, and modern DevOps practices.
Knowledge of data quality frameworks and monitoring tools.
Strong problem-solving skills and attention to detail in ensuring data reliability.
Effective communicator and team player, able to work in cross-functional environments.
Passion for data-driven decision-making and improving data infrastructure.