Remote LatAm Analytics Engineer for AI-Ready Data

Homeward; United States; Remote; USD 83,000 - 138,000; Full time

Benefits offered by this job

Fully remote (LatAm)

Overlap with US Central Time

Job summary

Homeward is seeking an Analytics Engineer to build and scale the data foundation that powers decision-making across the business. You will own core data pipelines and models, collaborating with analysts, product, and tech teams to ensure data is accurate, reliable, and consumable.

A key focus is reliability and AI-readiness—designing scalable data models with dbt, governing data, and improving observability while aligning with business needs. Remote LATAM-based with US Central overlap.

Qualifications

• Experience in analytics engineering, data engineering, BI, or similar data-focused role.
• Proficiency in SQL and dimensional data modeling, with scalable analytical datasets.
• Hands-on experience building and maintaining production data models and semantic layers using dbt.

Responsibilities

• Own the health and reliability of data pipelines, identifying issues and implementing durable solutions.
• Design, develop, test, and optimize scalable dimensional data models and data marts using dbt.
• Architect data environment for AI-readiness and ensure data is structured, governed, and accessible for AI use cases.
• Collaborate with Product and Technology teams on data dependencies and minimize disruption.
• Translate analytical needs into scalable solutions within our analytics platform.
• Develop domain expertise across Homeward's data models, metrics, and workflows.
• Establish data quality practices, monitoring, and documentation to improve confidence.

Skills

Analytics engineering

SQL

Data modeling

Python

Data governance

Communication

Problem solving

Stakeholder management

Tools

dbt

Looker

Hex

Tableau

Airflow

Python

AWS

Job description

Homeward is seeking an Analytics Engineer to build and scale the data foundation that powers decision-making across the business. You will own core data pipelines and models, collaborating with analysts, product, and tech teams to ensure data is accurate, reliable, and consumable.

A key focus is reliability and AI-readiness—designing scalable data models with dbt, governing data, and improving observability while aligning with business needs. Remote LATAM-based with US Central overlap.