Senior Data Engineer

Rhenus SE & Co. KG; Hilden; Hybrid; EUR 75.000 - 110.000; Vollzeit

Zusammenfassung

Rhenus SE & Co. KG seeks an experienced Azure Data Platform Engineer to develop, operate, and optimize a modern Azure-based data platform. You will focus on Azure, Databricks, data infrastructure, and CI/CD, supporting multi-tenant environments and enabling reliable, scalable data solutions.

The role involves designing end-to-end data solutions, building scalable ETL/ELT pipelines with PySpark, and collaborating with BI and data teams to ensure robust governance and secure data handling.

Qualifikationen

• Experience designing and operating modern Azure data platforms.

Aufgaben

• Design, build, and operate end-to-end data solutions using Azure services.
• Develop and maintain scalable ETL/ELT pipelines with PySpark.
• Support multi-tenant data platforms across environments with governance.
• Provision, configure, and maintain Azure data infrastructure for stability and security.
• Build CI/CD pipelines for data pipelines and Databricks workloads.
• Apply Azure best practices for performance and cost optimization.
• Collaborate with BI and data teams to support data models and reporting.
• Assist with data governance, access control, and basic metadata management.

Kenntnisse

Azure

Databricks

PySpark

CI/CD

Data platforms

Tools

Azure Data Factory

Azure Data Lake Storage Gen2

Databricks

Azure Synapse Analytics

Jobbeschreibung

About the Role:

We are looking for an experienced and solution-orientedAzure Data Platform Engineerto develop, operate, and optimize our modern Azure-based data platform. In this role, you will focus onAzure, Databricks, data infrastructure, and CI/CD, supportingmulti-tenant environmentsand enabling reliable, scalable data solutions.

Main responsibilities:

• Develop a Modern Azure Data Platform: Design, build, and operate end-to-end data solutions using Azure Data Factory, Azure Data Lake Storage Gen2, Databricks, and Azure Synapse Analytics.
• Create Data Pipelines: Develop and maintain scalable ETL/ELT pipelines using PySpark and Spark, with a strong focus on data quality, reliability, and performance.
• Multi-Tenant & Environment Support: Support and operate multi-tenant data platforms across multiple environments (development, test, production) with clear separation and governance.
• Infrastructure & Platform Operations: Provision, configure, and maintain Azure data infrastructure, ensuring stability, security, and scalability.
• CI/CD for Data Platforms: Build and maintain CI/CD pipelines for data pipelines and Databricks workloads, enabling automated deployments across environments.
• Cost-Efficient & Best-Practice Azure Usage: Apply Azure best practices to optimize performance and cost, including resource sizing, lifecycle management, and cost monitoring.
• Collaboration with BI & Data Teams: Work closely with BI and data teams to support efficient data models and reporting solutions.
• Data Governance & Security Basics: Support data governance requirements such as access control, secure data handling, and basic metadata management.