Description
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 .