The role involves designing, developing, and maintaining scalable data pipelines to ensure efficient data flow. Professionals in this position will build and optimize ETL/ELT processes to manage the ingestion and transformation of data from various sources. A key aspect of the work includes ensuring data quality, consistency, and availability while processing large volumes of structured and unstructured information. The position requires collaboration with analytics and business teams to translate requirements into technical solutions and define cloud-based data architectures. Additionally, the role involves documenting workflows and interacting directly with clients to propose value-driven solutions.

Candidates must hold a degree in Systems Engineering, Electronic Engineering, or a related field. The role requires three to five years of experience in designing, developing, and maintaining data solutions within analytical and productive environments. Applicants need solid proficiency in SQL, Python, Scala, and Apache Spark, alongside experience with cloud services and ETL frameworks. Furthermore, the position requires familiarity with AI tools and large language models to support development and technical problem-solving.