Data Engineers with ML OPS, AWS, EMR, and Sagemaker

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Job Overview

The Data Engineer with ML Ops at Executive Staff Recruiters / ESR Healthcare will play a pivotal role in designing, developing, and maintaining scalable data pipelines and infrastructure to support machine learning initiatives. This position requires collaboration with data scientists, software engineers, and other stakeholders to ensure that robust machine learning models are integrated and optimized in an AWS environment, leveraging services such as EMR and SageMaker. The ideal candidate will possess a strong understanding of data engineering practices while being proficient in machine learning operations, ensuring timely delivery and deployment of data solutions.

Job Responsibilities

• Design and implement data pipelines for real-time and batch processing of large datasets.
• Collaborate with cross-functional teams to understand data requirements and provide data-driven solutions.
• Optimize existing data architectures and processes for efficiency and scalability.
• Integrate machine learning models into production using AWS SageMaker and manage their lifecycle.
• Manage data storage solutions in AWS, ensuring security, reliability, and accessibility.
• Monitor and troubleshoot data pipeline performance and integrity.
• Document data workflows and contribute to best practices in data engineering and ML Ops.
• Stay current with emerging technologies and trends in data engineering and machine learning.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• 3+ years of experience in data engineering with a focus on machine learning operations.
• Hands-on experience with AWS services, particularly EMR, SageMaker, and S3.
• Proficient in programming languages such as Python, SQL, or Java.
• Strong understanding of data modeling, ETL processes, and data warehousing techniques.
• Experience with containerization technologies like Docker and orchestration tools such as Kubernetes is a plus.
• Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch) is highly desirable.

Technologies & Tools

The Data Engineer will utilize a variety of technologies and tools including, but not limited to, AWS services such as EMR, SageMaker, and S3. Proficient use of programming languages like Python and SQL will be required. The candidate will also work with database systems and data warehousing solutions, leveraging tools for data orchestration and monitoring. Familiarity with machine learning libraries and containerization technologies will enhance the capacity to manage ML Ops effectively.

Ideal Candidates

Ideal candidates for this position will exhibit strong analytical thinking and problem-solving skills, possessing the ability to communicate complex technical concepts to diverse audiences. A proactive approach to learning new technologies and a passion for data-driven decision-making are essential. Candidates should demonstrate solid teamwork capabilities, collaborating effectively with various stakeholders while maintaining attention to detail and commitment to quality in their deliverables.