Job Summary: We are seeking an Analytics Engineer to structure our data pipeline and ensure the technical foundation for developing dashboards and strategic analyses. Key Highlights: 1. Build, maintain, and evolve end-to-end data pipelines and data layers. 2. Ensure data quality, integrity, and traceability. 3. Collaborate with Product Owners and business areas. **About the Role** ================ We are seeking an Analytics Engineer to structure our data pipeline and ensure the necessary technical foundation for developing dashboards and strategic analyses. This person will be responsible for connecting diverse data sources, building robust and scalable models, and translating technical complexity into accessible and actionable business insights. **Responsibilities** ===================== * Build, maintain, and evolve end-to-end data pipelines and data layers (ingestion, transformation, modeling, and delivery for consumption). * Structure consistent consumption tables and analytical layers (e.g., facts, dimensions, reusable cleaned layers per product/client). * Apply business rules and unify taxonomies across multiple sources, ensuring consistency in metrics and definitions. * Ensure data quality, integrity, and traceability (audit, validate, monitor anomalies and unexpected variations). * Improve performance and efficiency of transformations and queries, avoiding manual rework and unnecessary costs. * Document models, calculation logic, and metric dictionaries clearly and accessibly for other teams. * Collaborate with Product Owners, technical teams, and business areas to align requirements, enable deliveries, and support real-world usage in dashboards, reports, and products. * Support analytics, data science, and product teams in correctly interpreting metrics, serving as the authoritative reference for official numbers. **Requirements** ============== * Strong proficiency in advanced SQL and analytical modeling; * Practical experience with data transformation/orchestration tools (e.g., dbt or equivalent) and versioning of business logic; * Experience in semantic standardization and taxonomies (normalizing entities and naming conventions across different data sources); * Hands-on experience with data validation and quality assurance (integrity tests, outlier/series-break detection, source auditing, historical consistency); * Understanding of performance and cost considerations in data environments (query optimization, reduction of unnecessary processing, storage/compute efficiency); * Ability to produce clear documentation of metrics, data dictionaries, and transformation rules for non-technical audiences; * Capability to work closely with Product and business areas, understanding what needs to be measured and translating that into reliable data modeling and delivery; * Familiarity with data governance best practices (traceability, change history, consistency across internal and external deliverables); * Prior experience with marketing and media data and metrics is considered a plus. **What We Offer** ==================== * Health Insurance * Wellhub * Hybrid or Remote Work \- Office in São Paulo \- SP.