Data Engineer (MLOps) - freelance

Client: Global Industrial Technology Company

I am seeking an experienced Data Engineer with strong MLOps capabilities for a 6-month remote engagement with a leading global player in industrial automation and digitalisation. This project focuses on optimising and scaling machine learning infrastructure for a next-generation industrial analytics platform used in manufacturing and energy systems.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines for ingesting and processing high-volume, real-time industrial data
• Collaborate with data scientists and software engineers to deploy and monitor ML models in production environments
• Implement CI/CD pipelines for model training, validation, and deployment
• Develop and manage infrastructure using tools such as Kubernetes, Docker, and Terraform
• Ensure compliance with data governance and security standards
• Automate workflows and improve reliability and efficiency of ML systems
• Troubleshoot issues across data ingestion, processing, and model serving layers

Required Skills:

• 5+ years of experience in data engineering, with proven MLOps project work
• Deep knowledge of data architectures, distributed systems, and streaming technologies (e.g., Kafka, Spark)
• Hands-on experience with MLOps tools and frameworks (MLflow, Kubeflow, Airflow, etc.)
• Proficient in Python and SQL
• Experience with cloud platforms (AWS, Azure, or GCP)
• Native German speaker, with excellent communication and documentation skills in both German and English

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Industries

  IT Services and IT Consulting, Financial Services, and Software Development

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