Data Platform Engineer H/F Step Up

We are looking for a highly skilled and hands-on Data Platform Engineer to join our Data fabric team. In this role, you will design, build, and maintain secure, scalable, and reliable data pipelines that support enterprise analytics and datadriven decisionmaking.
Collaboration with analysts, application teams, and security functions is essential to deliver robust data solutions aligned with corporate standards, and security requirements.
You will apply DataOps best practices-including CI/CD, version control, automated testing, and documentation-while supporting production environments through monitoring, troubleshooting, and continuous improvement.

Key responsibilities :

--> Data pipeline design & engineering
- Design, build, and maintain secure, scalable, and reliable data pipelines supporting enterprise analytics and datadriven decisionmaking.
- Collaborate with analysts, application teams, and cloud, infrastructure, and security teams to translate requirements into robust technical solutions.
- Develop and manage data ingestion, transformation, and integration processes using the DDSselected technology stack (MS Fabric, Azure, Terraform, some open source)
- Implement and maintain data models optimized for analytics, reporting, and downstream consumption.
- Apply engineering best practices including CI/CD, version control, automated testing, and documentation.
- Implement and maintain CI/CD for data workloads using GitHub integration and/or Azure DevOps pipelines.
- Use Infrastructure as Code (Terraform) for repeatable environment provisioning and controlled promotion across environments.

--> Platform reliability, quality & operations :
- Ensure data quality, consistency, availability, and performance across the data platform.
- Monitor, troubleshoot, and resolve issues in production data pipelines and platform components.
- Support operational activities such as incident management, performance tuning, and capacity planning.
- Contribute to continuous improvement of engineering standards and platform evolution

--> Enable and support internal data consumers :
- Provide onboarding, documentation, and best practices.
- Support analysts and application teams in using platform components.
- Contribute to governance (security, access models, data quality rules).