Data Engineer

EX Squared LATAM; Ciudad de México; A distancia; MXN 200,000 - 400,000; Jornada completa

Descripción de la vacante

A leading digital solutions company is seeking a Data Engineer to design and maintain data models for analytics-ready datasets. In this high-impact role, you'll contribute to a major data platform migration while ensuring data quality and collaborating with analysts. The ideal candidate has 3+ years of experience, advanced SQL skills, and familiarity with tools like Databricks and Snowflake. This position offers competitive compensation, flexible schedules, and the opportunity to work 100% remotely from anywhere in Latin America.

Servicios

Competitive USD compensation

100% remote work

Flexible schedules

Opportunities for continuous learning

Formación

• 3+ years of experience in analytics or data engineering.
• Familiarity with dimensional modeling and best data practices.
• Ability to communicate and work autonomously.

Responsabilidades

• Design high-quality data models for analytics.
• Build SQL transformations for dashboards.
• Ensure data quality during system changes.

Conocimientos

Advanced SQL

Data modeling

Communication skills

E-commerce data models

Data workflows

Herramientas

Databricks

Snowflake

BigQuery

Redshift

dbt

Descripción del empleo

Become an EXpert as an Data Engineer

At EX Squared LATAM, we connect top analytics and engineering talent across the region with innovative, data-driven projects. We’re looking for an Data Engineer who excels at building clean, scalable, analytics-ready datasets — ideally with experience in e-commerce data models.
This is a high-impact, high-autonomy role, contributing directly to a major data platform migration and the evolution of a modern analytics ecosystem.

What You’ll Do

• Design and maintain high-quality data models that transform raw data into analytics-ready datasets.

• Model e-commerce data (customers, orders, products, transactions) for reporting and analytics needs.

• Build, optimize, and document SQL transformations that power dashboards and decision-making.

• Work within a lakehouse environment (Databricks, Snowflake, BigQuery, Redshift) to structure and orchestrate scalable data pipelines.

• Ensure continuity and data quality when source systems or schemas evolve.

• Collaborate with analysts and engineers to translate business requirements into reliable data structures.

• Improve performance, documentation, and testing coverage across the data modeling ecosystem.

• Support BI and reporting layers by delivering well-designed, well-tested datasets.

What You’ll Bring

• 3+ years of experience in analytics engineering, data engineering, or similar roles (flexible with equivalent skill level).

• Advanced SQL — efficient, maintainable, and production-ready.

• Experience with Databricks, Snowflake, BigQuery, Redshift, or similar lakehouse/warehouse platforms.

• Understanding of dimensional modeling and data warehouse best practices.

• Experience working with e-commerce data models or operational datasets.

• Ability to communicate clearly, work autonomously, and make pragmatic technical decisions.

• Familiarity with modern data workflows, documentation, and testing practices.

• Strong plus (not required): experience working with Shopify data (customers, orders, products, transactions).

• Nice to have: dbt, BI tools, cloud infrastructure (Azure/AWS).

Why Join EX Squared?

EX Squared is a global digital solutions company powered by engineering, analytics, and innovation. Our LATAM team partners with leading clients on high-visibility, data-critical initiatives, including a major data platform migration where your modeling and engineering decisions will have direct business impact.
You’ll join a collaborative environment that values ownership, autonomy, and technical excellence.

What We Offer

• Competitive USD compensation aligned with technical seniority.

• 100% remote work from anywhere in Latin America.

• Flexible schedules and a people-first culture.

• Opportunities for continuous learning, engineering growth, and hands-on work with modern data technologies.