Summary: The Senior AWS Machine Learning Data Engineer will lead the design and implementation of data pipelines and machine learning infrastructure on AWS. This role involves collaboration with data scientists and product teams to deliver scalable ML solutions. The position is contract-based for 6 months with the possibility of extension, requiring a strong background in data engineering and AWS services. The ideal candidate will have extensive experience in operationalizing machine learning models and optimizing data processes.

Key Responsibilities:

• Architect and build scalable, secure, and maintainable data pipelines on AWS (Glue, Lambda, Step Functions, S3, Redshift, etc.)
• Operationalize machine learning models in production environments using SageMaker or custom deployment frameworks
• Automate and optimize ETL/ELT processes for structured and unstructured data
• Integrate CI/CD and MLOps best practices for rapid model iteration and deployment
• Collaborate across teams to align ML engineering efforts with business needs

Key Skills:

• 5+ years of data engineering experience, with 2+ years in a senior role
• Deep expertise with AWS services (S3, Glue, Lambda, SageMaker, Redshift, etc.)
• Strong Python and SQL skills; experience with PySpark a bonus
• Familiarity with containerization (Docker), orchestration (Airflow, Step Functions), and infrastructure as code (Terraform/CDK)
• Solid understanding of machine learning model lifecycle and best practices for deployment at scale
• Excellent communication skills and the ability to work independently in a remote environment

Salary (Rate): £600

City: London

Country: United Kingdom

Working Arrangements: undetermined

IR35 Status: inside IR35

Seniority Level: Senior

Industry: IT