Senior GCP DevOps Engineer (R-19673)

Shape the Future with Dun & Bradstreet

At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.

Key Responsibilities

• Engineer solutions on GCP foundation platform using Infrastructure as code methods (e.g. Terraform)
• Build and support continuous integration (CI), continuous delivery (CD) and continuous testing activities
• Implement optimizations in the cloud software development life cycle process to provide improvement in productivity, tools and techniques
• Embrace an automation-first approaches to testing, deployment, security and compliance of solutions through Infrastructure as Code and automated policy enforcement
• Empower the adoption of practices to minimize toil and manual work and increase automation and stability
• Collaborate across the different teams and areas such as cloud platform, security, data, risk & compliance areas to create cost effective optimum solutions for the business.

Key Skills

• Hands on experience in working with GCP/AWS and its services to create and implement cloud-based solutions using terraform
• Experience in creating automated CI/CD pipeline using Gitlab, Jenkins, Harness etc
• Experience with containerization, artifact repository, and orchestration technologies (such as Docker, Helm, Kubernetes, Mesos)
• Knowledge of containerization and container orchestration technologies such as GKE and Kubernetes is a must
• Experience in writing software in one or more languages, such as Java, Python, Go, JavaScript etc
• Experience maintaining internet facing production-grade applications in virtualized environments (cloud computing platforms and services)
• Experience managing internal or client-facing projects, troubleshooting clients' technical issues and working with engineering, sales and services teams and customers
• Experience in implementing data pipelines to automate the ingestion, transformation, and augmentation of data sources, and provide best practices for pipeline operations
• Experience automating infrastructure provisioning, DevOps, and/or continuous integration/delivery
• Certified in Google Professional Data Engineer/Solution Architect/AWS is a major advantage.