**Role: Data Engineer** **Work Model:** 100% remote **Employment Type:** Independent Contractor (PJ) **Schedule:** Flexible hours **Compensation:** To be discussed At **HW**, we are a publisher in the international natural supplements market, operating at the top of the global Direct Response space. We connect micro-influencers with consumers through affiliate marketing, offering full content support: copywriting, video editing, web design… All to maximize performance and scale! **We’re giants—and the proof is clear: our projected revenue of BRL 2 billion in 2025.** If you seek a collaborative and innovative environment, **HW** is the perfect place for you! **About the role:** The Senior Data Engineer will be responsible for designing, building, and evolving the company’s entire data architecture, ensuring efficiency, governance, and scalability across the information ecosystem. This professional will own data quality and operate end-to-end—from data ingestion and modeling to consumption by data products, reports, and Power BI dashboards. They must possess strong technical vision, sharp analytical capability, and a strategic perspective on how data impacts the business. Beyond technical expertise, the candidate must champion best practices, standardize processes, and collaborate with technology, product, and business teams—ensuring decisions are consistently grounded in reliable, well-structured data. **Key Responsibilities:** * Design, build, and maintain scalable and resilient data pipelines (ETL/ELT). * Implement data engineering best practices—including version control, testing, and process automation. * Design and optimize data models (relational and non-relational) to support analytics and reporting. * Integrate internal and external systems, connecting diverse data sources (APIs, databases, spreadsheets, SaaS tools, etc.). * Ensure data governance and quality by defining naming conventions, documentation standards, and validation rules. * Support business and BI teams in transforming data into actionable insights. * Create and maintain datasets and data models for Power BI, optimizing performance and usability. * Collaborate with backend and analytics teams to ensure consistency between transactional and analytical systems. * Propose and lead continuous improvements to data architecture and engineering practices. **Technical Requirements and Experience** * Proven experience in Data Engineering, Data Warehousing, or related fields. * Strong proficiency in SQL, Python, and ETL/ELT frameworks (Airflow, dbt, Prefect, etc.). * Experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, BigQuery, Snowflake, Redshift, ClickHouse, etc.). * Knowledge of data modeling methodologies (Kimball, Data Vault, Star Schema). * Experience integrating REST APIs and building ingestion pipelines. * Experience with visualization tools—especially Power BI. * Experience with version control (Git) and DevOps/DataOps best practices. * Familiarity with backend development (Node.js, Python, Go, or similar) and microservice integrations. * Preferred: Cloud infrastructure experience (AWS, GCP, or Azure) and data orchestration tools. **Soft Skills and Behavioral Profile** * Data-driven mindset and results orientation. * Ability to make technical decisions with product-oriented vision. * Autonomy, ownership mentality, and focus on continuous improvement. * Strong communication skills—both with technical and non-technical teams. * Collaborative profile, with willingness to share knowledge and mentor other team members. **Job Objectives (First 6 Months)** * Map and document the current data infrastructure. * Propose and implement a new, more efficient and scalable data architecture. * Standardize modeling, versioning, and integration practices. * Optimize Power BI and corporate reporting data models. * Reduce rework and inconsistencies across data sources. * Establish solid foundations for future Data Science and Machine Learning initiatives.