**The Challenge** We are looking for an **Analytics Engineer** to lead our organization’s data transformation engineering efforts. In this role, you will sit at the heart of the "Modern Data Stack", serving as the bridge between data engineering (infrastructure/ingestion) and business analytics (BI/Data Science). You will be challenged to architect the company’s reliable data layer, leveraging dbt and Python to transform raw transactional data into high-value analytical models. We seek a candidate who combines software engineering rigor (version control, testing, CI/CD) with strategic business vision. You will be responsible for ensuring that Product Squads and stakeholders make decisions based on an auditable, well-documented, and performant "Single Source of Truth". **What You’ll Do** * Develop and maintain data models using dbt (data build tool), applying best practices in modularity, documentation, and code reuse (macros/Jinja); * Architect the analytical data layer (Data Marts), transforming raw transactional source data into dimensional models (Star Schema/Snowflake) optimized for querying; * Ensure data lineage and automatic model documentation, facilitating enterprise-wide understanding of business rules; * Build and maintain complex orchestration pipelines using Apache Airflow (or similar), integrating Python scripts for data ingestion and manipulation when SQL alone is insufficient; * Manage the data lifecycle in modern data warehouses (e.g., Google BigQuery, Snowflake, or Redshift), focusing on partitioning strategies and cost-optimization for compute; * Implement a strong data testing culture (dbt tests, Great Expectations), ensuring integrity, uniqueness, and consistency before data reaches dashboards; * Structure the semantic layer for visualization tools such as Apache Superset (or Tableau/Looker), ensuring end users have access to standardized metrics; * Act as a technical mentor, elevating the team’s proficiency in advanced SQL and analytical engineering practices. **What We’re Looking For** * Bachelor’s degree in Computer Science, Engineering, Information Systems, or related fields; * Solid experience in the Data domain, specifically in Analytics Engineering or modern data modeling and transformation; * Advanced proficiency in dbt (Core or Cloud), including macro creation, custom tests, snapshots, and documentation generation; * Advanced SQL (Window Functions, UDFs, query optimization) and strong Python skills for automation and data engineering tasks; * Hands-on experience building DAGs and managing dependencies in Apache Airflow; * Experience working in cloud environments (Google BigQuery, AWS Redshift, or Snowflake); * Proficiency with Git/GitHub, code reviews, and CI/CD pipelines applied to data; * Ability to translate complex technical requirements into business stakeholder language; * Analytical mindset focused on troubleshooting in distributed data environments; * Autonomy to define architectures and mentor less senior professionals. **Bonus Points If You Have** * Knowledge of CRM and support platforms (HubSpot, Zendesk) and their data structures; * Experience with Product Analytics tools (Mixpanel, Amplitude, GA4) integrated into the data warehouse; * Prior experience building customer experience metrics (NPS, CSAT, Churn, LTV); * Familiarity with modern data transformation frameworks such as dbt (data build tool); * Knowledge of infrastructure-as-code (Terraform) applied to data infrastructure. **What You’ll Find Here** * A collaborative and dynamic environment that values innovation and growth; * A culture of continuous learning and accelerated development; * Opportunities to contribute to impactful projects affecting thousands of people daily; * Fully remote work model; * PJ (individual contractor) hiring arrangement. **Our Benefits** * Flex Food Swile – R$770/month * WeWork – access to coworking spaces across Brazil * Birthday day off * Fretonauta Talent referral program