Data Engineer and Advanced Analytics Specialist

Description

Job Summary: We are seeking an experienced data professional to join a team and enhance analytical capabilities by designing and implementing data management systems and advanced dashboards to transform business needs into data strategies. Key Highlights: 1. Design and implementation of large-scale data management systems 2. Interdisciplinary collaboration for clear data strategies 3. Promotion of best practices and expansion of team skills We seek an experienced data professional to integrate into a team and improve analytical capabilities. Key responsibilities include designing and implementing large-scale data management systems and advanced analytical dashboards. Data ingestion, transformation, and modeling processes will be optimized in both on-premises and cloud environments. The goal 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 needs 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 to expand the team’s data engineering skills are also expected. A proactive and solution-oriented attitude is valued for proposing improvements and new solutions that deliver business value through data. Professional fluency in English (written and spoken) is required to collaborate in international environments. A university degree (Bachelor’s, Licentiate, or Technical Engineering) in Mathematics, Engineering, Economics, or a related field—with a strong focus on quantitative analysis—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 table structures and data models—as well as experience in Finance or corporate financial processes—is a plus. Familiarity with Microsoft Fabric and/or Snowflake is advantageous. Knowledge of programming languages for data science or engineering (e.g., Python, R), and certifications or academic projects specialized in advanced analytics, are also valued.