Sr. Staff DevOps Engineer (Google Cloud Platform & Data/AI Focus)

 

Description:
This position will work closely with the Product Performance and Data and Analytics (DNA) teams on the Manufacturing Traceability (MFGT) project. They will be responsible for enabling Google Cloud Platform Infrastructure in both the AI and Data Analytics space, performing architectural design, review, and implementation via Terraform Cloud.

• Enable technologies and support the customer through operational readiness in DNA wrangle development environment
• Enable and support Spanner in mfg-dataanalytics and DNA wrangle environment.
• Enable Notebooks/DBT Python in DNA projects
• Enable Google Cloud Platform mfg-dataanalytics project to support Product Performance team innovation.
• Create and update Product Performance sandbox environments as necessary, cyclically improving and implementing based on customer demand.
• Assist in building DNA “Medallion Leveling” templates
• Assist in Landing Zone phase 2 enablement including implementation of AI feature flags, enhanced AI service templates, and create AI example sandboxes
• Work with Cloud Platform team to develop and implement a “lab” level environment strategy

Role Overview:
The selected contractor will work closely with:

• Manufacturing Traceability Team
• Data & Analytics Team
• Product Performance Team

Primary responsibilities include:

• Collecting and managing manufacturing process data
• Moving data into Google Cloud Platform (Google Cloud Platform)
• Building and managing cloud infrastructure
• Supporting analytics and reporting capabilities
• Developing infrastructure to support data movement and storage
• Assisting with implementation of AI-related technologies and services
• Establishing templates, standards, and best practices for deployment

Required Skills & Experience:
Must-Have Skills:

• Strong Google Cloud Platform (Google Cloud Platform) experience
• Terraform (Terraform Cloud strongly preferred)
• Cloud infrastructure and architecture expertise
• Data platform experience
• AI/Generative AI familiarity, particularly:
• Google Gemini Enterprise
• AI deployment best practices
• Security and governance considerations
• Scalable AI implementations

Preferred Google Cloud Platform Technologies:

• Experience with the following is highly desirable:
• BigQuery
• Dataplex
• Datastream
• Networking
• Storage
• VPCs
• Project administration and cloud architecture

Experience Requirements:

• Approximately 13+ years of cloud or cloud-related technology experience
• Deep Google Cloud Platform expertise is considered critical
• Azure experience is viewed as more transferable than AWS, but neither substitutes for strong Google Cloud Platform experience

AI Experience Clarification:
This is not primarily an AI developer role Instead, candidates should understand:

• AI platforms and services
• Gemini Enterprise offerings
• Deployment strategies
• Security considerations
• Governance and operational best practices
• AI implementation at scale

Industry Experience: Medical device or regulated-industry experience is preferred but not required.