**Description:** ---------------- **JOB MISSION** We are seeking a Data Engineer with an analytical orientation and business focus, responsible for integrating, transforming, and modeling data from multiple sources (SQL, NoSQL, and external APIs) for consumption in visualization tools and decision-making processes. This role combines technical data engineering capabilities with analytical skills and business understanding. **RESPONSIBILITIES** * Design and maintain data pipelines from SQL, NoSQL databases, and external APIs. * Model and transform data for analysis and visualization. * Build and maintain dashboards and reports in Power BI, Tableau, or MongoDB Charts. * Translate business requirements into metrics, KPIs, and data models. * Ensure data quality, consistency, and availability. * Automate processes using scripts and lightweight development. * Document data flows and analytical models. **Requirements:** --------------- **Education:** Bachelor’s degree in Systems Engineering, Computer Science, Data Engineering, or related field. **Experience:** 3+ years of experience as a Data Engineer or in data-related roles. Proven experience building data pipelines and working in cloud environments. **Technical Requirements:** * Solid experience with SQL databases (PostgreSQL, SQL Server, MySQL, or others). * Practical experience with NoSQL databases, preferably MongoDB. * Proficiency with at least one BI tool: Power BI, Tableau, or MongoDB Charts. * Scripting development capability (Python, JavaScript, or similar language). * Integration with REST APIs and handling of JSON/CSV formats. * Use of version control (Git). * Preferred: Knowledge of data warehousing and analytical modeling. **Desirable Certifications:** **✅AWS Certified Data Analytics or AWS Data Engineer Associate** **✅Google Professional Data Engineer** **✅Microsoft Certified: Azure Data Engineer Associate** **Skills:** Ability to interpret business needs and turn data into actionable insights. Analytical thinking and results orientation. Effective communication with both technical and business teams. Autonomy and judgment to ensure data quality.