Data Engineer at Judge Group

Location: REMOTE
Salary: $50.00 USD Hourly - $60.00 USD Hourly
Description:

Job Title: Data Engineer
Location: Remote (US Based)
Duration: 7+ month contract

Job Summary:
Our client is seeking a skilled Data Engineer to support the design, configuration, and maintenance of machine learning (ML) environments across on-premise and cloud platforms. This role involves close collaboration with cross-functional teams to ensure robust, secure, and scalable ML infrastructure.

Key Responsibilities:

Environment Management (On-Prem & Cloud)

• Design, configure, and maintain ML development and production environments
• Administer and troubleshoot Hadoop ecosystem components (HDFS, YARN, MapReduce)
• Perform Linux system administration, including shell scripting, service management, cron jobs, and log analysis
• Manage containerized environments using Docker and Kubernetes
• Monitor and optimize compute resources for ML training and inference workloads
• Ensure security, compliance, and version control across environments
• Automate data ingestion and preprocessing using tools like Apache Airflow or Azure Data Factory

Collaboration & Support

• Partner with DBAs, data scientists, ML researchers, and engineering teams to support the ML lifecycle
• Assist in deploying ML models to production and monitor performance
• Document processes and provide training and support to team members

Qualifications:

• Big Data: 1–2 years of experience with Hadoop (HDFS, YARN, MapReduce)
• System Administration: 1–2 years of Linux experience, including Bash scripting and troubleshooting
• Security: 1–2 years working with SSL, Kerberos, IAM, or similar protocols
• DevOps & Tools: 1–2 years using Docker and Git
• Programming: 1–4 years of Python experience for scripting and data engineering
• Cloud Platforms (Azure): 2–3 years of hands-on experience with:
  • Azure Data Factory
  • Azure Databricks
  • Azure Kubernetes Service (AKS)
  • Azure Machine Learning (AML)
• CI/CD & IaC: 2–3 years of experience with CI/CD pipelines and infrastructure-as-code practices

Preferred Qualifications:

• Experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker)
• Familiarity with ML libraries and techniques (e.g., deep learning, NLP, time-series forecasting)
• Understanding of data governance and monitoring tools

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Contact: kgregor@judge.com