DevOps & Data Pipeline Engineer

• Designing, implementing, and maintaining scalable and reliable DevOps infrastructures.
• You will be responsible for building and optimizing CI/CD pipelines (e.g., using Jenkins, GitLab or GitHub CI/CD) and if required additional automation solutions for the generation of applications, documentation, reports and deployment of tools.

Data Ingestion & Processing:

• Developing and implementing robust data ingestion pipelines that capture and process large volumes of data from various sources.
• You will ensure data quality and integrity, transform data for reporting and analytical purposes.

Standards-Compliant Documentation:

• Generating automated and reliable documents and reports and assessments, adhering to the requirements of the EN 50716 series of standards and subsequent norms.
• You will collaborate closely with subject matter experts to ensure the correct interpretation and implementation of standard requirements in technical solutions.

Security & Compliance:

• Ensuring that all developed tools and pipelines comply with Siemens' stringent cybersecurity standards and relevant industry standards.
• You will actively contribute to the implementation of security best practices within our processes.

Containerization & Batch Processing:

·Utilizing container and cloud technologies e.g., Docker, Kubernetes

Cross site Collaboration

·Collaborate closely with global engineering locations, esp. with headquarter in Germany.

Desired Skills:

• Several years (e.g., at least 8+ years) of relevant professional experience in a DevOps or Data Engineering role.
• Completed degree in Computer Science, Engineering, or a comparable field. Equivalent professional training with relevant experience will also be considered.
• Profound knowledge of Python for developing automation scripts and data processing pipelines.
• Extensive experience in designing, implementing, and maintaining CI/CD pipelines using Jenkins and/or GitLab/GitHub CI/CD.
• Practical experience with container technologies such as Docker.
• Experience with the development and optimization of batch/powershell processing workflows.
• Proven experience working with Snowflake for data integration, storage, and querying.
• Practical experience with DBT for data transformation and modeling in Snowflake.

Nice-to-have Skills:

• Experience with cloud platforms (AWS, Azure, GCP).
• Knowledge of Infrastructure as Code (IaC) tools like Terraform or Ansible.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana).
• Understanding of agile development methodologies.
• Experience with Kubernetes.
  • Strong Linux/Unix skills.