Senior Data Engineer (MLOps Engineer)
Tasks
- Build CI/CD workflows
- Build production machine learning services
- Collaborate in agile teams
- Communicate technical decisions
- Containerize applications with Docker
- Create automated deployment pipelines
- Deliver features for modeling and analytics
- Deploy real time API endpoints
- Design production data services
- Develop Infrastructure as Code with Terraform
- Develop monitoring for infrastructure health
- Develop monitoring for model performance
- Ensure scalability and reliability of ML systems
- Ensure security of ML systems
- Orchestrate containers with Kubernetes
- Perform data extraction and transformation
- Write production Python data pipelines
Perks/Benefits
- Contributory pension scheme
- Development days
- Discounts on insurance products
- Flexible working
- Hybrid working
- Pension scheme
- Retail discounts
- Volunteering days
Skills/Tech-stack
APIs | Azure DevOps | CI/CD | DBT | Docker | GitHub Actions | Infrastructure as Code | Kubernetes | Machine Learning | Microsoft Fabric | Monitoring | PySpark | Python | SQL | SQLMesh | Terraform | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Engineer | Engineer | MLOps Engineer | Senior Data Engineer
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