AWS Data Engineer
Posted 2 weeks ago by Experis UK
Negotiable
Inside
Hybrid
Knutsford, England, United Kingdom
Summary: We are looking for a Senior AWS Data & ML Engineer to join our team in Radbroke. This hybrid position involves working on advanced machine learning and data engineering projects using the latest cloud technologies. The role requires expertise in AWS, MLOps, and data pipelines, along with proficiency in Python and related tools. Candidates should have experience in both data engineering and machine learning engineering practices.
Key Responsibilities:
- Develop and implement data engineering and machine learning solutions using AWS technologies.
- Leverage MLOps practices to enhance the AI lifecycle.
- Collaborate on projects involving ECS, Sagemaker, and CI/CD tools like Gitlab and Jenkins.
- Monitor and deploy machine learning models in cloud environments.
- Work with big data ecosystems and ensure efficient data pipelines.
- Integrate backend services with RESTful APIs.
Key Skills:
- Expertise in AWS Data Engineering and ML Engineering.
- Proficiency in Python, Pyspark, and big data ecosystems.
- Hands-on experience with MLOps tools (e.g., MLflow, Airflow, Docker, Kubernetes).
- Experience in front-end development (HTML, Stream-lit, Flask).
- Familiarity with model deployment and monitoring in cloud environments.
- Understanding of the machine learning lifecycle and data pipelines.
- Experience with RESTful APIs.
Salary (Rate): undetermined
City: Knutsford
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: Senior
Industry: IT
AWS Date Engineer
Location: Radbroke (Hybrid - 2 days/week in office)
6 Months + Umbrella Only - Inside IR35
About The Role
We are seeking a highly skilled and experienced Senior AWS Data & ML Engineer to join our team in Radbroke. This hybrid role offers the opportunity to work on cutting-edge machine learning and data engineering projects, leveraging the latest cloud technologies and MLOps practices.
Required / Primary Skills
- AWS Data Engineering
- ML Engineering
- ML-Ops
- ECS, Sagemaker
- Gitlab
- Jenkins CI/CD
- AI Lifecycle
- Experience in front-end development (HTML, Stream-lit, Flask)
- Familiarity with model deployment and monitoring in cloud environments (AWS).
- Understanding of machine learning lifecycle and data pipelines.
- Proficiency with Python, Pyspark, Big-data ecosystems
- Hands-on experience with MLOps tools (e.g., MLflow, Airflow, Docker, Kubernetes)
Secondary Skills
- Experience with RESTful APIs and integrating backend services
All profiles will be reviewed against the required skills and experience. Due to the high number of applications we will only be able to respond to successful applicants in the first instance. We thank you for your interest and the time taken to apply!