Job Summary: We are seeking a Junior Data Engineer with solid experience in cloud architecture—especially AWS and Databricks—to develop scalable data pipelines. Key Highlights: 1. Solid experience in cloud architecture and Databricks. 2. Development of Spark jobs in batch and streaming using Python. 3. Advanced knowledge of Data Engineering and ETL processes. **Position: Junior Data Engineer****Employment Type: CLT** **Work Mode: Remote** **Education: Bachelor’s degree in IT** **Mandatory Requirements / Technologies / Required Knowledge** **Main Responsibilities** Strong expertise in cloud architecture technologies, with emphasis on Databricks and its tools (Unity Catalog, Delta Lake, Databricks Workflows, SQL Editor, Jobs, DLT, etc.); Experience in cloud-based projects, preferably on AWS, integrated with Databricks for scalable data pipelines; Experience developing Spark jobs in batch mode and Spark Streaming, using Databricks Notebooks in Python for data manipulation and transformation; Advanced knowledge of Data Engineering, including hands-on experience with ETL (Extract, Transform, Load) processes and their variations within the Databricks environment; Experience in relational and dimensional data modeling; Knowledge of relational databases such as Db2 and SQL Server; Integration between relational databases and Databricks using JDBC. DESIRABLE TECHNICAL KNOWLEDGE: Knowledge of data replication solutions, especially in environments leveraging \*Databricks \* for real-time management of large-scale data volumes; Participation in Data Lake implementation and governance projects; Proficiency in Scala for development and programming in distributed environments; Familiarity with data analytics and machine learning tools such as R and SAS; Knowledge of MPP databases, such as Netezza \* or \*Redshift .