About this role
Engineer responsible for modernizing and operating Cognos and Power BI platforms using Kubernetes, Terraform, GitHub, and Microsoft Fabric.
We are looking for a BI Platform & Cloud Analytics Engineer to design, deploy, and operate enterprise reporting platforms such as IBM Cognos Analytics and Microsoft Power BI / Fabric using cloud-native, automated, and scalable platform technologies. This role bridges BI, Cloud Infrastructure, Kubernetes, and DevOps, enabling secure, highly available, and modern analytics platforms.
Key Responsibilities
· Deploy, manage, and support Cognos Analytics (VM-based and containerized)
· Support Power BI Service, Power BI Gateways, and Microsoft Fabric
· Build and manage BI infrastructure using Infrastructure as Code (Terraform)
· Deploy and operate BI workloads on Kubernetes, Red Hat OpenShift, and ARO
· Implement CI/CD pipelines using GitHub for BI and platform deployments
· Manage YAML-based configurations for Kubernetes/OpenShift workloads
· Enable hybrid and cloud analytics architectures (On-prem ↔ Cloud)
· Support Cognos to Power BI / Fabric migration initiatives
· Ensure platform security, RBAC, monitoring, and operational stability
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Required Skills
· Experience with IBM Cognos Analytics
· Strong experience with Power BI Service
· Working knowledge of Microsoft Fabric (Lakehouse, Warehouse, Semantic Models)
· Hands-on experience with Kubernetes
· Experience with Red Hat OpenShift / Azure Red Hat OpenShift (ARO)
· Strong experience with Terraform (IaC)
· Experience using GitHub for version control and CI/CD
· Proficiency in YAML configuration files
· Understanding of cloud platforms (Azure preferred)
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Nice to Have
· Cognos SDK / extensions
· Power BI Deployment Pipelines
· BI platform migration experience
· Cost optimization / FinOps exposure
· SRE or platform operations experience
· 5–9 years overall experience
· 3+ years in BI platform, cloud, or analytics engineering roles
Success Criteria
· Stable, secure, and scalable BI platforms
· Automated deployments with minimal manual intervention
· Faster BI release cycles
· Successful modernization toward Power BI & Fabric