DevOps Engineer

Requisition Number: 76190

The company built on breakthroughs. ​  
Join us.​  

Corning is one of the world’s leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what’s possible.  ​  

How do we do this? With our people. They break through limitations and expectations – not once in a career, but every day. They help move our company, and the world, forward. ​  

​At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.​   

​Come break through with us.  

The global Information Technology (IT) Function is leading efforts to align IT and Business Strategy, leverage IT investments, and optimize end to end business processes and associated information integration technologies.  Through these efforts, IT helps to improve the competitive position of Corning's businesses through IT enabled processes.  IT also delivers Information Technology applications, infrastructure, and project services in a cost efficient manner to Corning worldwide.

Corning is seeking a Databricks Platform Engineer / DevOps/Administrative Specialist to help design, build, automate, and support our enterprise Data Analytics Platform on AWS. This role will enable scalable data engineering, analytics, machine learning, and AI / Generative AI / RAG capabilities across the organization.

Responsibilities

• Architect, engineer, and administer Databricks on AWS for enterprise-scale analytics and AI workloads.
• Build and maintain secure, scalable platform capabilities using Terraform, GitLab CI/CD, and AWS services.
• Manage Databricks workspaces, clusters, jobs, policies, and Unity Catalog governance.
• Collaborate with AI / GenAI / RAG developers to enable and support platform capabilities for AI / GenAI / RAG, including document ingestion, embeddings, vector search, and model endpoint integration.
• Collaborate with data scientists, data engineers, and other stakeholders to enable and support MLOps processes including MLflow, model lifecycle management, and deployment automation.
• Implement monitoring, logging, security, and operational support to ensure reliability and performance.
• Collaborate with architecture, infrastructure, security, data engineering, and AI/ML teams to deliver enterprise platform standards.

Qualifications

• Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
• 5+ years of experience in cloud platform engineering, DevOps, data platforms, or related roles.
• 3+ years of hands-on experience with Databricks.
• Strong experience with cloud platforms (AWS, Azure, GCP), Terraform, and GitLab CI/CD.