Experteer Overview

Siga leyendo para descubrir lo que necesitará para tener éxito en este puesto, incluyendo habilidades, cualificaciones y experiencia.
In this role you will build and maintain scalable data ingestion and transformation pipelines using Databricks, PySpark and SQL, enabling reliable data for downstream applications. You will collaborate with cross-functional teams to evolve lakehouse datasets and ensure data quality and timeliness. You contribute to automated testing, troubleshoot pipelines in QA and production, and optimize Spark workloads. This international, hands-on role offers growth as you help advance AXON Networks' data platform in telecom.

Compensaciones / Ventajas
• Develop and maintain scalable data ingestion and transformation pipelines using Databricks, PySpark and SQL
• Build and maintain Databricks Jobs and Workflows for data ingestion and processing
• Evolve datasets across the lakehouse layers, managing schema changes and data contracts while keeping data traceable to upstream sources
• Ensure data quality and freshness,



making datasets reliably available to downstream consumers within the required processing windows
• Develop and maintain automated tests for data pipelines, including unit, integration and regression testing
• Troubleshoot data pipeline issues in QA and production, identify root causes and implement fixes
• Improve the performance and efficiency of Spark jobs and data transformations

Responsabilidades
• B.Sc./M.S. Computer Science or related field
• 2+ years of professional experience in Data Engineering or a similar role
• Hands-on experience with Python, PySpark and SQL
• Good understanding of data modeling and lakehouse xghoner concepts
• Familiarity with automated testing and Git-based development workflows
• Strong analytical and problem-solving skills, with the ability to troubleshoot data processing issues
• Fluency in both English and Spanish
• Ability to work in hybrid in Madrid

Requisitos principales

📌 Data Engineer (Madrid)
🏢 AXON-Networks
📍 Madrid