Overview
We are seeking a Senior BI & Analytics Engineer with deep Power BI expertise to lead the analytics and semantic layer of an enterprise Azure data platform.
This role sits on top of a modern Lakehouse architecture built with Azure Data Factory, ADLS Gen2, Databricks, and Delta Lake. You will own how curated datasets are modeled, governed, deployed, and consumed across the organization.
This is not a reporting support role. It is an analytics engineering leadership role focused on metric integrity, deployment discipline, semantic consistency, and production reliability. You will partner closely with Azure Integration Engineers and Data Engineers to ensure Gold-layer datasets are analytics-ready, performant, and trusted.
Responsibilities
Analytics Architecture & Modeling
• Lead design and development of enterprise-grade Power BI semantic models and datasets.
• Define KPI standards, metric governance, naming conventions, and documentation practices.
• Ensure consistency of measures across dashboards, workspaces, and user personas.
• Design scalable data models optimized for Databricks-backed Lakehouse environments.
Delivery & Ownership
• Own analytics delivery from requirements through production release.
• Translate complex business needs into structured, decision-ready dashboards.
• Review and approve BI artifacts produced by other developers.
• Serve as the accountability point for data accuracy and analytics trust.
Environment & DevOps Discipline
• Establish and manage Dev / Test / Prod workspace segregation in Power BI.
• Lead deployment and controlled promotion of artifacts across environments.
• Implement CI/CD practices for Power BI using source control and deployment pipelines.
• Support rollback and controlled release strategies for analytics assets.
Platform Collaboration
• Partner with Databricks engineers to shape analytics-ready Gold datasets.
• Ensure correct grain, performance optimization, and semantic alignment.
• Collaborate with integration and platform teams on access control and security models.
• Implement row-level security (RLS) and governance controls aligned with enterprise standards.
Performance & Reliability
• Ensure dashboards perform efficiently at scale.
• Proactively identify model inefficiencies, performance bottlenecks, and metric inconsistencies.
• Maintain reliability and production readiness across analytics assets.
Required Qualifications
• 8+ years of experience in BI, analytics engineering, or data visualization roles.
• Deep hands-on experience with Power BI in enterprise production environments.
• Strong experience building and managing semantic models, DAX measures, and optimized datasets.
• Experience working with Databricks or Lakehouse-style architectures as backend sources.
• Strong SQL skills and deep understanding of joins, grain, and performance implications.
• Experience implementing Dev / Test / Prod separation and controlled deployments.
• Experience with CI/CD concepts applied to BI platforms.
• Strong understanding of governance, access control, and row-level security.
• Ability to translate ambiguous stakeholder needs into structured analytics solutions.
• Availability during MST working hours.
Preferred Qualifications
• Experience working in Azure-based enterprise data environments.
• Familiarity with Delta Lake and Medallion architecture concepts.
• Experience with near-real-time or high-volume analytics scenarios.
• Experience coordinating with integration engineers and cloud architects.
• Experience mentoring BI developers or leading analytics standards initiatives