Sr. Analytics Engineer (Brazil and Argentina Only)

Role overview

A senior analytics engineering position is open on a Core Data Engineering team for candidates based in Brazil or Argentina, with all interviews conducted remotely and applications accepted in English only. The role centers on architecting enterprise data models, translating raw data into business-ready datasets, and leading the next generation of the analytics platform and semantic capabilities. The hire will report to the Data Engineering Manager and serve as a technical leader shaping data quality, governance, and self-service analytics across the organization.

Responsibilities

- Partner with cross-functional executive stakeholders to translate business strategy into a robust analytics architecture with embedded governance and self-service capabilities - Architect, document, and maintain Kimball dimensional models, standardized metric definitions, warehouse transformation logic, and scalable BI datasets for high-stakes decision-making - Design and govern production-grade models powering the enterprise semantic layer, enabling AI/ML integrations and business-wide self-service analytics - Establish and enforce data quality standards, automated testing, lineage tracking, cost optimization, and alerting across dbt transformation pipelines - Refactor legacy business logic and fragmented query architectures into modular, scalable semantic pipelines while driving metric standardization and secure access controls - Mentor junior and mid-level engineers on technical best practices and serve as a subject matter expert for analytics engineering projects

Requirements

- Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field, or equivalent practical experience - 6+ years of experience in analytics engineering, data engineering, or enterprise data modeling, including production-grade transformation workflows - Expertise applying dimensional modeling techniques such as Star Schema and Kimball methodology, along with dbt and semantic layer tools for standardizing metric logic - Hands-on experience modeling complex business domains including Salesforce, Google Analytics, ad platforms, product usage metrics, and JSON data for enterprise BI consumption - Strong software engineering background with advanced Git workflows, CI/CD practices, modular architecture design, and thorough code documentation - Advanced proficiency in SQL, dbt (including macros, packages, and performance tuning), Snowflake, Python, and modern BI platforms such as Looker or Tableau

Nice to have

- Deep familiarity with Google Analytics, marketing and social media ad platforms, CRM/Salesforce systems, and designing custom semantic metrics at scale - Comprehensive understanding of modern data stack architecture, transformation strategies, automated testing, governance frameworks, and BI integrations

Benefits and work setup

- Remote-only interview process with accommodations available to support a comfortable candidate experience - Structured interview flow including a 30-minute talent acquisition screen, 30-minute hiring manager video interview, 30-minute team interview, and 90-minute technical interview