Data Engineer: Cloud & ML Pipelines | Flexible Hours, WFH

PALFINGER; Bergheim; Hybrid; EUR 55.000 - 67.000; Vollzeit

Benefits dieser Stelle

Flexible hours

PALfit health program

Company restaurant with meals

Job ticket

Employee discounts

Zusammenfassung

PALFINGER is seeking a Data Engineer to join its Digital Solutions team. You will design and maintain scalable data pipelines and cloud-based architectures to transform machine and process data into valuable business insights.

You will collaborate with data scientists, engineers, and business experts to enable data-driven decision making. The role requires hands-on experience with SQL, Python/Pandas, Spark, and cloud platforms (Azure/AWS/GCP), plus knowledge of DataOps and MLOps practices.

Qualifikationen

• Bachelor's or Master's degree in Computer Science, Engineering, Business Informatics, or a related technical field, with hands-on data processing experience.
• Strong expertise in SQL, Python/Pandas, Spark, Azure Data Factory, and scalable data models/architectures.
• Experience with cloud environments (Azure, AWS, GCP) and modern data platforms (data warehouses, data lakes).
• Familiarity with CI/CD, Git, Scrum/Kanban; knowledge of Databricks is a plus; English in international environments.

Aufgaben

• Design, build, and maintain scalable data pipelines integrating data from diverse sources and cloud platforms.
• Develop cloud-based data architectures and data provisioning for analytics and ML use cases.
• Ensure data quality and reliability with monitoring, testing, and DataOps practices.

Kenntnisse

SQL

Python/Pandas

Spark

Azure Data Factory

Databricks

English fluency

Agile methodologies

Ausbildung

Bachelor's or Master's in CS/Engineering/Business Informatics

Tools

Azure

AWS

GCP

Databricks

Terraform

Azure Bicep

Jobbeschreibung

PALFINGER is seeking a Data Engineer to join its Digital Solutions team. You will design and maintain scalable data pipelines and cloud-based architectures to transform machine and process data into valuable business insights.

You will collaborate with data scientists, engineers, and business experts to enable data-driven decision making. The role requires hands-on experience with SQL, Python/Pandas, Spark, and cloud platforms (Azure/AWS/GCP), plus knowledge of DataOps and MLOps practices.