Data Engineer

Description

Job Summary: The Data Engineer will be a key player in building an integrated data ecosystem, structuring the company's data platform to support strategic decision-making. Key Highlights: 1. Structure a value-oriented data platform (Data Lake) 2. Build an integrated data ecosystem for analytics and AI 3. Develop and maintain reliable and scalable data pipelines Data Engineer to structure the company's data platform (Data Lake), ensuring reliable, scalable, and value-oriented pipelines. This person will be a key player in building an integrated data ecosystem (sales, after-sales, inventory, finance, and CRM), supporting strategic decisions and analytics and AI initiatives. Key Responsibilities Design, develop, and maintain data pipelines (ETL/ELT) Integrate data from multiple sources: DMS (Dealer Management System) ERP CRM Automaker / marketplace APIs Build and maintain Data Lake / Data Warehouse (e.g., BigQuery) Ensure data quality, consistency, and governance Optimize query performance and costs Structure data models (layers: raw, trusted, refined) Create analytical datasets for BI consumption (Power BI) Implement pipeline monitoring and observability Automate data flows and integrations Support analysts and data scientists with reliable datasets Required Qualifications Solid SQL experience (advanced) Data modeling experience Experience with orchestration tools (e.g., Airflow) Experience with cloud-based data pipelines (preferably GCP / BigQuery) Proficiency in programming languages such as Python Experience with ETL/ELT processes Knowledge of version control (Git) and engineering best practices * Preferred Qualifications (highly valued in the automotive context) Experience with: Dealer DMS systems: Linx Apollo or NBS CRM data and sales funnel data Knowledge of: BigQuery (partitioning, clustering, cost optimization) Dataform / dbt REST APIs and integrations Streaming experience (Kafka / PubSub) Knowledge of data security and governance (LGPD)