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Senior Lead BI Platforms (Power BI & Cognos) Engineer @ EXL

Pune, Maharashtra, INOnsiteFull-time
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About this role

Role Overview

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

Experience Level

· 4–12 years overall experience

· 3+ years in BI platform, cloud, or analytics engineering roles

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Success Criteria

· Stable, secure, and scalable BI platforms

· Automated deployments with minimal manual intervention

· Faster BI release cycles

· Successful modernization toward Power BI & Fabric

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