Data Engineer (MLOps) - freelance

Cognitive Group | Part of the Focus Cloud Group; Dach; Remote; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A global industrial technology company seeks an experienced Data Engineer with strong MLOps capabilities for a 6-month remote project. The role involves designing and maintaining scalable data pipelines, collaborating with teams to deploy ML models, and ensuring compliance with data governance standards. Ideal candidates will have over 5 years of experience in data engineering and MLOps, with proficiency in Python, SQL, and cloud platforms.

Qualifikationen

• 5+ years of experience in data engineering, with proven MLOps project work.
• Deep knowledge of data architectures, distributed systems, and streaming technologies.
• Hands-on experience with relevant MLOps tools and frameworks.

Aufgaben

• Design and maintain scalable data pipelines for real-time industrial data.
• Collaborate with data scientists and engineers to deploy and monitor ML models.
• Implement CI/CD pipelines for model training, validation, and deployment.

Kenntnisse

Data engineering

MLOps

Python

SQL

Cloud platforms (AWS, Azure, or GCP)

Kubernetes

Docker

Terraform

Tools

Kafka

Spark

MLflow

Kubeflow

Airflow

Jobbeschreibung

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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