• As a Cloud Engineer, your focus is on implementing modern data and AI infrastructures, orchestrating GPU clusters, structuring data platforms, and automating pipelines for efficient model training and stable operation of inference interfaces.
• You design data platforms, from storage architecture and Lakehouse formats to the integration of orchestration and streaming components.
• You set up tools like Airflow, Spark on Kubernetes or Ray, integrate them together and ensure that data and ML workflows run reliably in production.
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Main tasks at a glance

• They build, operate, and continuously optimize data pipelines in Microsoft Fabric, using Data Factory tools and Spark-based workloads.
• Your responsibilities include the development and implementation of ELT/ETL processes for the integration of various source and target systems, as well as ensuring data quality, performance, and comprehensive monitoring throughout the entire data flow.
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