Das ist der Job
Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines for batch and real‑time data processing.
Darum lohnt es sich
Implement data workflows on Databricks using Spark, ensuring high performance and reliability. Deploy and manage cloud infrastructure on Microsoft Azure and/or AWS, including storage, compute, and networking resources. Integrate SAP Datasphere and other SAP data sources into the data lake/warehouse architecture.
Monitor, troubleshoot, and optimize data pipelines to meet SLA and cost‑efficiency targets. Requirements Several years of professional experience as a Data Engineer building cloud‑native data pipelines. Strong hands‑on expertise with Databricks, Azure and/or AWS services.
Proven knowledge of ETL/ELT concepts, batch processing, and streaming technologies (e.g., Spark Structured Streaming). Experience integrating SAP data platforms such as SAP Datasphere is highly desirable. Degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
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