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

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Written by AI from the job title and company, not by Executive Staff Recruiters / ESR Healthcare, so some details may not match this job. The employer's own page has the real description.

Position Overview

The Data Engineer with expertise in ML Ops, AWS, EMR, and SageMaker will be a pivotal member of the data team at Executive Staff Recruiters / ESR Healthcare. This role involves designing, developing, and maintaining scalable data pipelines and machine learning workflows that enable robust data analysis and enhance decision-making processes. The ideal candidate will collaborate with data scientists, analysts, and other stakeholders to ensure that the infrastructure meets the varying data requirements of the organization, facilitating efficient deployment of machine learning models and optimizing data processing workflows.

Job Responsibilities

• Design and implement data pipelines that support the collection, storage, and processing of large datasets.
• Develop and optimize machine learning workflows within AWS environments, specifically using SageMaker and EMR.
• Collaborate with data scientists to ensure seamless model deployment and integration into production environments.
• Monitor and troubleshoot data pipelines to maintain high performance and reliability.
• Implement data security practices to comply with healthcare regulations and ensure data integrity.
• Create documentation for data processes, infrastructure, and workflow for knowledge sharing across teams.
• Participate in code reviews and contribute to the continuous improvement of the data engineering team's practices.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Minimum of 3 years of experience in data engineering, with specific expertise in ML Ops.
• Proficient in AWS services, particularly EMR, SageMaker, and related data management tools.
• Strong programming skills in languages such as Python, Java, or Scala.
• Experience with data pipeline frameworks like Apache Spark or Apache Airflow.
• Understanding of machine learning concepts and modeling techniques.
• Excellent problem-solving skills and the ability to work independently as well as part of a team.

Technologies & Tools

The position will primarily utilize a suite of technologies and tools centered around AWS and machine learning platforms. These include Amazon Web Services (AWS) for cloud computing, Amazon EMR for big data processing, Amazon SageMaker for building, training, and deploying machine learning models, along with data processing frameworks such as Apache Spark and Apache Airflow for orchestrating workflows. Familiarity with SQL and NoSQL databases, alongside tools for data visualization, will further enhance the scope of this role.

Ideal Candidates

Ideal candidates will possess a strong analytical mindset coupled with a keen attention to detail and a proactive approach to problem-solving. They will demonstrate effective communication skills, enabling them to interact successfully with cross-functional teams. A perfect fit will also be someone who thrives in a fast-paced environment, exhibits adaptability to changing priorities, and maintains a commitment to delivering high-quality data solutions. Enthusiasm for continuous learning and staying updated with the latest industry trends in data engineering and machine learning is highly valued.