Position Summary: We are seeking a data professional to enhance analytical capabilities by designing and implementing data management systems and advanced dashboards, optimizing processes, and collaborating to transform business needs into clear data strategies. Key Highlights: 1. Design and implementation of large-scale data management systems 2. Interdisciplinary collaboration for data strategies 3. Use of Microsoft Fabric, Snowflake, and Power BI We seek an experienced data professional to join our team and strengthen analytical capabilities. Key responsibilities include designing and implementing large-scale data management systems and advanced analytical dashboards. Processes for data ingestion, transformation, and modeling will be optimized across on-premises and cloud environments. The objective is to build and deploy efficient and secure solutions using tools such as Microsoft Fabric, Snowflake, and Power BI. Close collaboration with other departments will be required to translate business and financial requirements into clear data strategies, establishing robust databases enabling organization-wide information access. Maintaining high standards of quality and compliance across all analytical activities is essential. Knowledge sharing and promotion of best practices are expected to expand the team’s data engineering capabilities. A proactive, solution-oriented attitude is valued for proposing improvements and new data-driven solutions that deliver business value. Professional fluency in English (written and spoken) is required to collaborate effectively in international environments. A university degree (Bachelor’s, Licentiate, or Technical Engineering) in Mathematics, Engineering, Economics, or a related field with a strong quantitative analytics focus is mandatory. Advanced proficiency in Microsoft Excel—including data modeling, complex formulas, and advanced analytics—is expected. Advanced SQL skills—focused on querying, transforming, and optimizing large volumes of data—are essential. Solid understanding of ETL (extraction, transformation, loading) processes—including integration with diverse sources and destinations—is desirable. Advanced experience with SAP—particularly regarding table structures and data models—as well as experience in Finance or corporate financial processes is advantageous. Familiarity with Microsoft Fabric and/or Snowflake is a plus. Knowledge of data science or engineering programming languages (e.g., Python, R) and specialized academic certifications or projects in advanced analytics will be considered favorably.