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

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Job Overview

The Data Engineer with Machine Learning Operations (ML Ops) at Executive Staff Recruiters / ESR Healthcare will play a critical role in designing, building, and maintaining scalable data pipelines to support the organization’s data-centric initiatives. This individual will collaborate closely with data scientists and IT teams to deploy machine learning models and ensure data integrity and accessibility on cloud platforms, particularly AWS, utilizing technologies like EMR and SageMaker. The ideal candidate will demonstrate proficiency in handling large datasets and implementing data engineering best practices to optimize processing workflows and enhance data driven decision making.

Job Responsibilities

• Design, develop, and maintain robust and scalable data pipelines.
• Implement and manage ML Ops processes to facilitate the deployment of machine learning models in production.
• Utilize AWS services such as S3, EMR, and SageMaker for efficient data storage, processing, and model deployment.
• Collaborate with data scientists to understand data requirements and translate them into operational pipelines.
• Optimize data workflows for performance and cost-effectiveness.
• Monitor and troubleshoot data processes to ensure seamless operations and timely delivery of insights.
• Document data engineering processes, standards, and best practices.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field; Master's degree preferred.
• 3+ years of experience in data engineering, with a focus on ML Ops.
• Proficiency in AWS technologies, particularly EMR, S3, and SageMaker.
• Strong programming skills in Python, Java, or Scala.
• Experience with data modeling, ETL processes, and database management.
• Familiarity with containerization tools such as Docker and orchestration tools like Kubernetes is a plus.
• Excellent analytical and problem-solving abilities.
• Strong communication and collaboration skills.

Technologies & Tools

The Data Engineer will primarily utilize technologies including AWS EC2 for cloud compute, Amazon S3 for storage solutions, Amazon EMR for big data processing, and Amazon SageMaker for deploying and managing machine learning models. Additional tools for data processing include Spark and Hadoop, while version control will be managed through Git. Familiarity with monitoring and logging platforms, such as CloudWatch, will also be advantageous.

Ideal Candidates

The ideal candidates for this position will be innovative thinkers with a proactive approach to problem-solving. They will possess a strong passion for data and technology, coupled with a desire to drive improvements in data engineering methodologies. Candidates should demonstrate strong collaboration skills and a commitment to delivering high-quality outputs in a fast-paced environment. A mindset focused on continuous learning and adaptation to new technologies will further enhance their fit for the expanding capabilities of our data-driven initiatives.