Senior Analytics Engineer (100% Remote) (LATAM Only)

Allshore Talent · Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Guyana, Mexico, Paraguay, Peru, Suriname, Uruguay, Venezuela · $23.75 – $25 · posted today ago

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About this role

About AllShore Talent

AllShore Talent is a leading remote staffing company, offering top-tier professionals working 100% remote to businesses worldwide. Specializing in IT and software development, design, administrative support, digital marketing, and more. AllShore connects organizations with skilled talent to meet diverse business needs.

About The Role

Our client is expanding its modern data and analytics capabilities and is seeking a Senior Analytics Engineer with strong expertise in analytics engineering, dimensional data modeling, DBT, and cloud-based data platforms. This role is heavily focused on designing and building scalable analytical data models that support reporting, business intelligence, and modern analytics initiatives across internal departments. Candidates should have strong hands-on experience with dimensional modeling concepts such as facts, dimensions, star schemas, and Kimball methodology, along with practical experience using Databricks and cloud analytics tooling.

The ideal candidate is a strong SQL and analytics engineering professional who can work independently, communicate effectively with stakeholders, and deliver production-ready data solutions in enterprise environments.

Requirements

Key Responsibilities

Analytics Engineering & Data Modeling (Primary Focus)

Design and implement scalable analytical data models using dimensional modeling best practices
Build and maintain fact tables, dimension tables, star schemas, and reporting datasets
Develop and manage DBT transformations, models, and analytics workflows
Create scalable ELT pipelines using Databricks, SQL, Python, and cloud-based technologies
Collaborate with stakeholders to translate business and reporting requirements into reliable data solutions
Ensure data quality, consistency, and governance across analytics environments
Support modern analytics initiatives using Microsoft Fabric, SQL endpoints, and related tooling
Use Terraform or Infrastructure as Code (IaC) tooling to manage data platform resources
Contribute to AI-enabled analytics initiatives, integrations, and modern data platform enhancements.

Secondary Responsibilities

Provide light support for legacy Microsoft reporting environments (SSRS), on an as-needed basis only.

Required Qualifications (in priority order)

Strong hands-on experience with DBT and analytics engineering workflows, including deep expertise in dimensional data modeling:
- Facts and dimensions
- Star schema design
- Kimball methodology
- Analytical warehouse modeling
Hands-on experience with Databricks, including SQL, Python, and PySpark; advanced SQL skills for data transformation and analytics engineering
Experience using Terraform or Infrastructure as Code (IaC) tooling
Experience with Microsoft Fabric, especially SQL endpoints and analytics workloads
Experience supporting AI-enabled analytics initiatives, copilots, agents, or modern AI integrations — candidates who can help teams adopt AI tooling are a strong differentiator for this client
Strong communication and stakeholder-management skills
Ability to work independently in a fast-paced remote environment

Nice-to-Have Skills

Familiarity with Power BI or enterprise reporting environments
Experience modernizing legacy BI/data environments
Familiarity with Azure Data Factory, Synapse, or related Microsoft cloud analytics services
Experience with data quality frameworks, monitoring, or testing practices

Who You Are

You are an analytics-focused data professional with strong business and technical understanding
You excel at translating reporting and analytics requirements into scalable data models
You are comfortable working independently and collaborating across multiple teams
You bring strong ownership, communication, and problem-solving skills
You are confident explaining technical concepts to both technical and non-technical stakeholders

Non-Technical Requirements (weighted equally to technical skills)