TL;DR

Data Engineer (Data Analysis): Design, build, and optimize scalable data pipelines and models for analytics and business insights with an accent on ETL/ELT automation, data modeling, and integration. Focus on developing reliable, high-quality data solutions, troubleshooting pipeline issues, and collaborating cross-functionally in a hybrid environment.

Location: Hybrid in Mexico City, Mexico

Company

%hirify_global% is a leading global cloud-based software company specializing in customer relationship management (CRM) and enterprise software solutions.

What you will do

Design, build, and maintain automated ETL/ELT pipelines using 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 and contribute to continuous improvement of data engineering processes.

Requirements

Location: Must be based in Mexico City or able to work hybrid there
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, Snowflake, Informatica, and Apache Airflow.
Strong experience in data analytics, data curation, and data modeling techniques.
Familiarity with CI/CD workflows, Git, and modern DevOps practices.