Senior Analytics Engineer, Brazil, Argentina

Niche

. Architect, build, and scale enterprise data models, translating complex raw data into clean, business-ready datasets .

Posted 9/18/2026full-timeRemote • Brazil, ArgentinaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and maintaining enterprise data models, focusing on data accuracy, governance, and scalable BI solutions. Proficient in advanced data transformation workflows and semantic layer implementations, with a strong foundation in analytics engineering and data modeling techniques.

Highest-signal resume keywords

Dimensional Data ModelingDbtSQLSnowflakeData Governance

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Hard Skills

Data EngineeringEnterprise Data ModelingData TransformationSemantic Layer ImplementationAutomated TestingRoot-Cause AnalysisModular Architecture DesignCode DocumentationBusiness IntelligenceData Quality

Soft Skills

MentoringCollaborationCommunication

Tools & Technologies

LookerTableauGoogle AnalyticsGitCI/CD

Industry Keywords

Kimball MethodologyStar SchemaJSONMarketing PlatformsCRM/Salesforce

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

Architect, build, and scale enterprise data models, translating complex raw data into clean, business-ready datasets
Drive data accuracy, documentation, observability, semantic consistency, and warehouse performance
Lead the design and maintenance of modular dbt models, semantic layers, and BI views
Partner with executive stakeholders to translate business strategy into analytics architecture, governance, and self-service capabilities
Architect and maintain Kimball dimensional models, standardized metric definitions, warehouse transformation logic, and scalable BI datasets
Design and govern production-grade models powering the enterprise semantic layer and AI/ML integrations
Establish data quality, automated testing, lineage tracking, cost optimization, and alerting across dbt pipelines
Refactor legacy business logic and fragmented query architectures into scalable semantic pipelines
Drive data governance, metric standardization, secure access controls, and mentor junior and mid-level engineers
Lead analytics platform workstreams, own domain models, conduct root-cause analysis, and shape the technical roadmap
Report to the Manager, Data Engineering (Core)

Requirements

What you’ll need

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
Proven track record of architecting, deploying, and maintaining mission-critical, production-grade data transformation workflows and enterprise semantic models
Expertise in dimensional data modeling techniques (Star Schema, Kimball methodology), dbt, and advanced semantic layer tools
Extensive experience modeling complex business domains, product usage metrics, and unstructured/semi-structured data (JSON) for enterprise BI consumption
Strong software engineering background applied to data, including advanced git workflows, CI/CD, modular architecture design, and comprehensive code documentation
Advanced proficiency in SQL, dbt, Snowflake, Python, Git, and modern BI platforms such as Looker or Tableau
Deep expertise with Google Analytics, marketing/ad/social media platforms, CRM/Salesforce systems, and custom semantic metrics
Comprehensive understanding of modern data stack architecture, transformation strategies, semantic layer implementation, automated testing, governance, and BI integrations
Only applications/resumes written in English will be accepted