Cloud Platform Engineer / GCP / Remote

• Strong experience with Google Cloud Platform (GCP) services and architecture
• Hands-on expertise with Terraform, including building and maintaining modules
• Experience working with Terraform Cloud or similar remote state management tools
• Solid background in DevOps and cloud platform engineering
• Experience developing and supporting CI/CD pipelines, preferably with GitHub Actions
• Familiarity with Cloud Run or container-based workload execution in GCP
• Experience designing and implementing cloud landing zones or environment templates
• Strong understanding of infrastructure as code best practices
• Ability to collaborate closely with data and analytics teams in an enablement capacity
• Experience working across multiple environments such as development, UAT, and production

Desired Skills & Experience

• Exposure to BigQuery, Dataplex, or other GCP data ecosystem tools
• Familiarity with Gemini or other GCP AI/ML tooling
• Experience supporting data platforms or analytics-focused teams
• Understanding of data ingestion and processing workflows
• Exposure to Kubernetes in other environments
• Background in manufacturing or highly data-driven industries
• Ability to operate effectively in fast-paced, evolving environments

A leading medical device company is seeking a Cloud Platform Engineer to support large-scale data initiatives within a manufacturing environment. This role focuses on building and scaling infrastructure in Google Cloud Platform, with an emphasis on Terraform, DevOps practices, and enabling data-driven teams across the organization. The position is fully remote within the U.S.

This opportunity is centered around a high-impact initiative tied to manufacturing traceability and product performance analytics. You’ll play a key role in enabling teams that are actively improving product reliability using real-world manufacturing data. The environment is fast-moving and collaborative, where the priority is building flexible, reusable infrastructure that empowers data and analytics teams to experiment, iterate, and deploy quickly. This is an ideal role for someone who enjoys working across multiple teams, building foundational systems, and operating in an environment where not everything is fully defined yet.