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

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Job Overview

As a Data Engineer with expertise in Machine Learning Operations (MLOps) at Executive Staff Recruiters / ESR Healthcare, you will be pivotal in building and managing scalable data pipelines that support the deployment of machine learning models. You will work closely with data scientists and analysts to ensure that data architecture is robust and optimized for high-quality data ingestion, transformation, and analysis. In addition, your role will include leveraging AWS services such as EMR and Sagemaker to enhance the organization’s data capabilities, ensuring efficient operations and maintaining high standards of data governance and security.

Job Responsibilities

• Design, construct, and maintain scalable data pipelines in a cloud environment, particularly using AWS services.
• Collaborate with data scientists and software engineers to optimize machine learning models for performance and scalability.
• Implement MLOps practices to enhance the lifecycle management of machine learning models.
• Utilize AWS EMR to process big data sets and facilitate distributed data processing.
• Implement data governance and security measures to ensure data integrity and compliance with relevant regulations.
• Monitor and troubleshoot data pipeline performance to ensure timely data delivery.
• Conduct data quality assessments and manage data cleansing processes.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Data Science, or a related field.
• 3+ years of experience in data engineering and working with machine learning applications.
• Proficient in AWS tools, specifically EMR, Sagemaker, and related services.
• Strong programming skills in Python, SQL, or Java.
• Experience with data warehousing solutions and big data technologies (e.g., Hadoop, Spark).
• Familiarity with MLOps frameworks and practices.
• Excellent analytical, problem-solving, and communication skills.

Technologies & Tools

The position utilizes a variety of technologies and tools to facilitate data engineering and machine learning operations. Key tools include Amazon Web Services (AWS) EMR for big data processing, AWS Sagemaker for building, training, and deploying machine learning models, along with databases such as SQL, Hadoop, and Spark. Knowledge of data orchestration tools and version control systems such as Git is also beneficial.

Ideal Candidates

Ideal candidates for this role will demonstrate a strong foundation in data engineering principles and a proactive attitude towards implementing best practices in MLOps. They should possess a keen analytical mindset, an intrinsic motivation to solve complex data challenges, and the ability to collaborate effectively within a team environment. A strong desire for continuous learning and keeping up with the latest data technologies will also be crucial for success in this position.