Data Engineering Coordinator (#)

Description

We are seeking a Data Engineering Manager to lead and develop our team of data engineers, responsible for building and optimizing data pipelines, architectures, and processes that support strategic and advanced analytics. This professional will be a key player in driving the adoption of ELT tools and preparing the team for the future by incorporating Artificial Intelligence as a fundamental component of data solutions. **Key Responsibilities** * Team management: lead, guide, and develop data engineers, ensuring high-quality deliveries aligned with the company’s strategic objectives. * Data architecture and infrastructure: define and implement scalable solutions in Data Warehouses and Data Lakes. * Governance and security: ensure data quality, security, and reliability. * Process optimization: monitor, automate, and optimize data pipelines and flows, guaranteeing performance and availability. * Data strategy and AI: identify opportunities to apply artificial intelligence and automation to increase efficiency and value delivered by the team. * Collaboration with business areas: translate strategic needs into clear and effective technical solutions. **Technical Requirements** * Solid experience with ELT/ETL tools (Alteryx, Power Query, Talend or similar). * Proficiency in SQL and Python (libraries such as pandas, matplotlib, etc.). * Knowledge of BI tools (Power BI, Tableau). * Experience in cloud environments (preferably OCI). * Experience with data architecture (Data Warehouse, Data Lake, pipelines). * Preferred: familiarity with customer data and CRM platforms. **Leadership and Behavioral Profile Requirements** * Autonomy and strategic vision to manage complex deliveries. * Clear communication, translating technical problems into business solutions. * Proactivity and innovation, anticipating trends and proposing improvements. * Prior experience leading data engineering teams or related functions. **Differentiators** * Experience applying Artificial Intelligence to data processes (e.g., pipeline automation, MLOps, AI-assisted data quality). * Track record of transforming teams to adopt emerging technologies. **Profile of professionals under your management — they work with:** * Developing analytical routines and pipelines in Python, R, or Scala; * Exploring and processing large volumes of data; * Extensive PL\-SQL knowledge; * Building dashboards and reports in Power BI, Tableau, or QlikView; * Cloud-based data environments on OCI.