Analytics Engineer (LatAm only)

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

Descripción de la vacante

A global digital solutions company is seeking an Analytics Engineer to design and maintain high-quality data models using Shopify data, advanced SQL, and Databricks. The role requires 4+ years of experience in analytics engineering and involves collaborating with teams to improve data quality and efficiency. This position offers competitive USD compensation, 100% remote work opportunities, and a flexible schedule within a people-first culture focused on continuous learning and modern data technologies.

Servicios

Competitive USD compensation

100% remote work from anywhere in Latin America

Flexible schedules

Opportunities for continuous learning

Formación

• 4+ years of experience in analytics engineering, data engineering, or similar roles.
• Advanced SQL skills — able to write efficient, maintainable, production‑ready SQL.
• Strong experience with Databricks or similar platforms (lakehouse architecture).

Responsabilidades

• Design and maintain high‑quality data models that transform raw data into analytics‑ready datasets.
• Build and optimize SQL transformations to support reporting and analytics needs.
• Collaborate with analysts and engineers to translate business requirements into reliable data structures.

Conocimientos

SQL

Databricks

E-commerce data models

Dimensional modeling

Data workflows

Descripción del empleo

Become an EXpert as an Analytics Engineer (Shopify + SQL + Databricks)

At EX Squared LATAM, we connect top analytics and engineering talent across the region with innovative, data-driven projects. We’re looking for an Analytics Engineer with strong experience working with Shopify data, advanced SQL, and expertise in Databricks.

This is a high-impact role for someone who can build reliable, well-structured data models and support fast-growing analytics teams with clean, scalable datasets.

What You’ll Do

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

• Model Shopify data including customers, orders, products, and transactional objects for business reporting.

• Build and optimize SQL transformations to support reporting, dashboards, and downstream analytics needs.

• Work with Databricks (or a similar lakehouse environment) to structure, orchestrate, and document scalable data pipelines.

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

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

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

• Support dashboards and reporting tools by delivering well‑designed, well‑tested datasets.

What You’ll Bring

• 4+ years of experience in analytics engineering, data engineering, or similar roles.

• Advanced SQL skills — able to write efficient, maintainable, production‑ready SQL.

• Strong experience with Databricks or similar platforms (lakehouse architecture, Delta, notebooks, pipelines).

• Understanding of dimensional modeling and data warehouse best practices.

• Experience working with e‑commerce data models and operational datasets.

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

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

• Nice to have (not required): experience with 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 works with leading clients on high‑visibility projects where data quality and modeling make a real business impact. You’ll join a collaborative environment that values ownership, continuous learning, 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 working with modern data technologies.