As a Data Engineer, you will build the data pipelines that enable our digital transformation. You will be responsible for the clean, reliable, and scalable flow of data between hundreds of ERP systems and our modern data architecture.

Data Pipeline Engineering: You will design and implement robust ETL/ELT pipelines that reliably extract, transform, and load data from hundreds of ERP systems. You will utilize modern orchestration tools and ensure that everything runs smoothly, even with complex data flows. You will build pipelines that are not only functional but also maintainable and extensible.

Data Lake & Data Warehouse Architecture: You will help build our data lake infrastructure on AWS from the ground up. This includes structuring data effectively, implementing data governance concepts, and ensuring that data is optimally prepared for analytics and business intelligence. You understand the difference between raw, staging, and curated data and implement the corresponding architectures.

Greenfield Project – Legacy System Integration: You'll be right in the middle of an exciting greenfield project: the integration of several hundred legacy ERP systems. This is no standard integration – it involves complex data structures, different formats, and the challenge of creating a consistent data model from heterogeneous sources.

Workflow Orchestration & Reliability: You'll implement resilient workflows for time-critical data processing. You'll utilize modern orchestration patterns and ensure that pipelines continue to run or restart smoothly, even in the event of errors. You'll build monitoring and alerting systems so that problems are detected before they lead to actual outages.

Collaboration & Development: You'll work closely with our Staff Engineer, the Product Owners, and the approximately 10-person development team. You'll learn from experienced colleagues while contributing your own ideas. You'll grow with the challenges and continuously develop your skills.

• Data Quality & Documentation: You implement data quality checks and ensure that poor-quality data never enters our systems. You document data flows and transformation logic so that others understand what happens to the data.

As a Data Engineer, you will build the data pipelines that enable our digital transformation. You will be responsible for the clean, reliable, and scalable flow of data between hundreds of ERP systems and our modern data architecture.

Data Pipeline Engineering: You will design and implement robust ETL/ELT pipelines that reliably extract, transform, and load data from hundreds of ERP systems. You will utilize modern orchestration tools and ensure that everything runs smoothly, even with complex data flows. You will build pipelines that are not only functional but also maintainable and extensible.

Data Lake & Data Warehouse Architecture: You will help build our data lake infrastructure on AWS from the ground up. This includes structuring data effectively, implementing data governance concepts, and ensuring that data is optimally prepared for analytics and business intelligence. You understand the difference between raw, staging, and curated data and implement the corresponding architectures.

Greenfield Project – Legacy System Integration: You'll be right in the middle of an exciting greenfield project: the integration of several hundred legacy ERP systems. This is no standard integration – it involves complex data structures, different formats, and the challenge of creating a consistent data model from heterogeneous sources.

Workflow Orchestration & Reliability: You'll implement resilient workflows for time-critical data processing. You'll utilize modern orchestration patterns and ensure that pipelines continue to run or restart smoothly, even in the event of errors. You'll build monitoring and alerting systems so that problems are detected before they lead to actual outages.

Collaboration & Development: You'll work closely with our Staff Engineer, the Product Owners, and the approximately 10-person development team. You'll learn from experienced colleagues while contributing your own ideas. You'll grow with the challenges and continuously develop your skills.

• Data Quality & Documentation: You implement data quality checks and ensure that poor-quality data never enters our systems. You document data flows and transformation logic so that others understand what happens to the data.