As a (Senior) Cloud Data Engineer (m/f/d), you will work closely with clients and teams to strategically design and implement solution-oriented cloud solutions. You will take ownership of your projects, communicate clearly with various stakeholders, and integrate new technologies from the areas of cloud, AI, and automation into projects in a targeted and practical manner.

• You design and implement scalable cloud data platforms for analytics, AI, and automation use cases.
• You will develop high-performance ETL/ELT pipelines as well as modern lakehouse and data warehouse architectures with a focus on data quality, governance, and observability.
• You will implement and further develop technological solutions based on Azure, AWS, Databricks, Microsoft Fabric, Spark and streaming services to create future-proof platforms.
• You analyze business requirements and translate them into secure, efficient, and AI-enabled data architectures.
• You work closely with clients and interdisciplinary teams and actively shape DataOps, CI/CD and automation approaches.
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As a (Senior) Cloud Data Engineer (m/f/d), you will work closely with clients and teams to strategically design and implement solution-oriented cloud solutions. You will take ownership of your projects, communicate clearly with various stakeholders, and integrate new technologies from the areas of cloud, AI, and automation into projects in a targeted and practical manner.

• You design and implement scalable cloud data platforms for analytics, AI, and automation use cases.
• You will develop high-performance ETL/ELT pipelines as well as modern lakehouse and data warehouse architectures with a focus on data quality, governance, and observability.
• You will implement and further develop technological solutions based on Azure, AWS, Databricks, Microsoft Fabric, Spark and streaming services to create future-proof platforms.
• You analyze business requirements and translate them into secure, efficient, and AI-enabled data architectures.
• You work closely with clients and interdisciplinary teams and actively shape DataOps, CI/CD and automation approaches.
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