Data Engineer - (AWS/MLOps/Python/PySpark/Sagemaker/ECS/Gitlab/CI/CD/Banking/Fintech)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with expertise in AWS, MLOps, Python, and PySpark, focusing on data pipeline development in a hybrid location. Key skills include ECS, Sagemaker, CI/CD practices, and experience in banking/fintech. Contract length and pay rate are unspecified.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
-
🗓️ - Date discovered
August 27, 2025
🕒 - Project duration
Unknown
-
🏝️ - Location type
Hybrid
-
📄 - Contract type
Unknown
-
🔒 - Security clearance
Unknown
-
📍 - Location detailed
Knutsford, England, United Kingdom
-
🧠 - Skills detailed
#Big Data #Cloud #Spark (Apache Spark) #ML (Machine Learning) #Model Deployment #Airflow #SageMaker #AI (Artificial Intelligence) #GitLab #AWS (Amazon Web Services) #Docker #MLflow #Data Engineering #Jenkins #Monitoring #Flask #Deployment #PySpark #Kubernetes #HTML (Hypertext Markup Language) #Data Science #Python #Data Pipeline #Streamlit
Role description
Job Title: Data Engineer - (AWS/MLOps/Python/PySpark/Sagemaker/ECS/Gitlab/CI/CD/Banking/Fintech) Location: Knutsford (Hybrid)
Job Description:
We are seeking an experienced Data Engineer with strong expertise in AWS, MLOps, and data pipeline development. The ideal candidate will have hands-on experience in deploying, monitoring, and maintaining machine learning models in cloud environments, as well as proficiency in big data ecosystems and CI/CD pipelines.
Key Responsibilities:
• Design, develop, and optimize data pipelines to support AI/ML workloads.
• Build and manage solutions using AWS services including ECS and Sagemaker.
• Implement MLOps practices with tools such as MLflow, Airflow, Docker, and Kubernetes.
• Collaborate with data scientists and engineers to streamline the machine learning lifecycle.
• Integrate backend services via RESTful APIs and support front-end frameworks (HTML, Streamlit, Flask).
• Ensure CI/CD best practices using GitLab, Jenkins, and related tools.
Key Skills:
• Primary Skills: AWS Data Engineering, ML Engineering, MLOps, ECS, Sagemaker, GitLab, Jenkins, CI/CD, AI Lifecycle, Front-end (HTML, Streamlit, Flask), Cloud model deployment/monitoring
• Technical Skills: Python, PySpark, Big Data ecosystems
• MLOps Tools: MLflow, Airflow, Docker, Kubernetes
• Secondary Skills: RESTful APIs, Backend integration
Job Title: Data Engineer - (AWS/MLOps/Python/PySpark/Sagemaker/ECS/Gitlab/CI/CD/Banking/Fintech) Location: Knutsford (Hybrid)
Job Description:
We are seeking an experienced Data Engineer with strong expertise in AWS, MLOps, and data pipeline development. The ideal candidate will have hands-on experience in deploying, monitoring, and maintaining machine learning models in cloud environments, as well as proficiency in big data ecosystems and CI/CD pipelines.
Key Responsibilities:
• Design, develop, and optimize data pipelines to support AI/ML workloads.
• Build and manage solutions using AWS services including ECS and Sagemaker.
• Implement MLOps practices with tools such as MLflow, Airflow, Docker, and Kubernetes.
• Collaborate with data scientists and engineers to streamline the machine learning lifecycle.
• Integrate backend services via RESTful APIs and support front-end frameworks (HTML, Streamlit, Flask).
• Ensure CI/CD best practices using GitLab, Jenkins, and related tools.
Key Skills:
• Primary Skills: AWS Data Engineering, ML Engineering, MLOps, ECS, Sagemaker, GitLab, Jenkins, CI/CD, AI Lifecycle, Front-end (HTML, Streamlit, Flask), Cloud model deployment/monitoring
• Technical Skills: Python, PySpark, Big Data ecosystems
• MLOps Tools: MLflow, Airflow, Docker, Kubernetes
• Secondary Skills: RESTful APIs, Backend integration
