Job Description

IT is different here. Our work as technology specialists pushes the boundaries of what’s possible in health care. You will build solutions that make a real difference in people’s lives. Driven by the importance of their work, our team members innovate to elevate. We’re encouraged to be curious, collaborate, and turn ideas into solutions that can make health care better for all.

As a Principal DataOps to MLOps Engineer, you will play a pivotal role in bridging the gap between data operations and machine learning operations. You will be responsible for designing, implementing, and maintaining the infrastructure and processes that support the dataops to MLOps lifecycle - data ingestion, governance and processing supporting model deployment and monitoring.

If you are ready to make a career out of making a difference, then you are the person for this team.

What You Will Do:

Infrastructure Development: 

Design and implement scalable MLOps supportive data pipelines for data ingestion, processing, and storage. Support and maintain DataOps components of cloud infrastructure to support machine learning workflows. Ensure data quality, availability, and reliability throughout its lifecycle. 

Model Deployment and Monitoring: 

Collaborate with data scientists to deploy DataOps supporting the lifecycle of machine learning models into production environments. Set up monitoring and alerting systems to track model performance and data drift. Automate DataOps in support of model retraining and deployment processes to ensure continuous integration and delivery. 

Collaboration and Leadership: 

Work closely with cross-functional teams, including data engineers, data scientists, and DevOps engineers. Provide technical leadership and mentorship to junior engineers. Drive best practices for DataOps and MLOps within the organization. 

Process Optimization: 

Implement and optimize CI/CD pipelines for DataOps to machine learning projects. Develop and enforce standards for version control, testing, and documentation. Identify and address bottlenecks in data and model workflows to improve efficiency. 

Security and Compliance: 

Ensure compliance with data privacy and security regulations. Implement robust security measures to protect data and models. 

What You Bring:

Bachelor's Degree or Advanced Degree where required8+ Years of ExperienceIn lieu of degree, 10+ years exp.Extensive experience in DataOps and MLOps, with a strong understanding of both domains. Proficiency in languages such as Python, SQL, Scala, Glue, with Ab Initio a plus  Hands-on experience with cloud platforms (AWS, Snowflake with Ab Initio a plus) and containerization technologies such as Docker Strong understanding of CI/CD for data engineering and QitHub methods Strong knowledge of machine learning frameworks and libraries (Sagemaker and Snowpark ML) Excellent problem-solving skills and the ability to work in a fast-paced environment. Strong communication and leadership skills. Strong understanding of Metadata driven workflows, data architecture, semantics and data governance 

Preferred Qualifications: 

Experience with Snowflake cloud platform, AWS, Sagemaker, Ab Initio and Ataccama. Understanding of data governance and compliance frameworks. Previous experience in a leadership or principal engineer role. 

Why Join Us: 

Opportunity to work on cutting-edge technologies and innovative projects. Collaborative and inclusive work environment. Competitive salary and benefits package. Professional development and growth opportunities 

Salary Range

$143,100.00 - $259,900.00