As a Data Engineer with PySpark, you will:- Design, develop, and maintain scalable and reliable data processing solutions using PySpark.- Build and manage robust batch and streaming data pipelines.- Develop efficient data transformation and processing solutions using Python, PySpark, and SQL.- Design, develop, and optimize data models to support scalable and high-performance data processing.- Work with large datasets and complex data processing workloads.- Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and scalability.- Implement data quality, validation, and error-handling mechanisms across data pipelines.- Collaborate with engineering, architecture, and business teams to deliver reliable data solutions.- Contribute to Agile development practices and continuously improve data engineering standards and processes.What You Bring to the Table:- 5+ years of professional experience in Data Engineering or a related field.- Strong hands-on experience with PySpark as a core data processing technology.- Strong proficiency in Python, PySpark, and SQL.- Hands-on experience developing and maintaining batch and streaming data pipelines.- Experience working with large-scale data processing and transformation.- Good understanding of data modeling, data integration, and data optimization.- Experience with cloud-based data platforms and modern data engineering architectures.- Experience with data quality, validation, troubleshooting,



and performance optimization.- Familiarity with CI/CD and modern software engineering practices.- Experience working in Agile development and delivery environments.- Strong communication, collaboration, analytical, and problem-solving skills.You Should Possess the Ability to:- Develop scalable and high-performance data pipelines using PySpark.- Build efficient data transformations using Python, PySpark, and SQL.- Process and manage large volumes of structured and unstructured data.- Optimize Spark jobs, data processing performance, and resource utilization.- Troubleshoot complex data pipeline and processing issues.- Design reliable and maintainable data engineering solutions.- Implement data quality and validation processes.- Work effectively with technical and business stakeholders.- Apply best practices for code quality, scalability, maintainability, and reliability.- Continuously improve data engineering processes and solutions.What We Bring to the Table:- Opportunity to work on enterprise-scale data engineering initiatives in Spain.- Exposure to modern data platforms, PySpark, cloud technologies, and large-scale data processing.- A collaborative Agile environment focused on technical excellence and innovation.- Opportunities to work on complex data pipelines and data transformation solutions.- Continuous learning and opportunities for technical and professional growth.- A culture focused on quality, ownership, scalability, and sustainable data engineering solutions.#J-18808-Ljbffr

📌 Data Engineer With Pyspark (Madrid)
🏢 Zohorecruit
📍 Madrid