Senior Analyst - BI Development

Position Summary

The Analyst II - Data Analytics serves as an enterprise technical authority for Power BI performance, shared semantic models, access architecture, and business intelligence engineering practices. Operating as part of an offshore analytics hub, this role is responsible for the performance, reliability, scalability, security, and maintainability of enterprise BI products and the semantic models that support them.

The role partners closely with the Consulting Data Architect at the interface between curated SQL data structures and the semantic layer. Together, these roles design and deliver reusable enterprise semantic models, define data and access requirements, resolve cross-layer performance and modeling issues, and ensure that data structures, relationships, calculations, security, refresh processes, and governed business metrics operate as an integrated solution.

The Consulting BI Developer also partners with the onshore BI Lead to develop, govern, and continuously improve the enterprise analytics design system, technical standards, reusable components, and development practices. The role provides advanced technical guidance, reviews complex solutions, resolves ambiguous or enterprise-impacting issues, and enables distributed development teams to deliver consistent, governed, secure, and high-performing analytics products.

Responsibilities

Consulting-Level Ownership Enterprise Delivery Leadership

• Own the technical performance, reliability, scalability, security, and maintainability of enterprise Power BI products and shared semantic models.
• Lead complex or enterprise-impacting BI deliverables and technical workstreams with limited oversight, from architecture and solution design through development, validation, release, monitoring, enhancement, and retirement.
• Identify technical risks, performance constraints, security concerns, data limitations, architectural dependencies, and delivery issues early and recommend practical mitigation actions.
• Provide technical direction, peer review, coaching, and escalation support to BI developers and distributed delivery teams without direct people-management responsibility.

Enterprise Semantic Model Ownership

• Design, develop, optimize, govern, and maintain shared enterprise semantic models that support multiple analytics products, business functions, and stakeholder groups.
• Define and implement appropriate model grain, dimensions, relationships, hierarchies, measures, calculation groups, aggregations, partitions, row-level security, and object-level security.
• Develop and govern reusable DAX measures, calculation patterns, naming conventions, business terminology, and semantic-model components.
• Reduce duplicated models, inconsistent calculations, unmanaged measures, fragmented reporting logic, and inconsistent access rules through reusable and governed semantic-layer solutions.

Enterprise BI Performance Platform Reliability

• Monitor and improve query performance, report responsiveness, refresh duration, model size, memory utilization, capacity consumption, concurrency, and overall user experience.
• Diagnose DAX formula-engine and storage-engine performance, model cardinality, relationship behavior, calculation dependencies, query patterns, and resource-intensive report interactions.
• Use DAX Studio, Power BI Performance Analyzer, VertiPaq Analyzer, Tabular Editor, ALM Toolkit, XMLA endpoints, Microsoft Fabric monitoring capabilities, and comparable approved tools to inspect, troubleshoot, compare, optimize, and maintain semantic models.
• Establish performance baselines, monitoring practices, diagnostic procedures, alerting approaches, and service expectations for enterprise BI products.

Analytics Design System Reusable Standards

• Partner with the onshore BI Lead to develop, govern, and continuously improve the enterprise analytics design system.

Data Architecture SQL-Layer Partnership

• Partner with the Consulting Data Architect to define the interface between curated SQL data structures and the enterprise semantic layer.
• Collaborate on analytical model grain, conformed dimensions, fact structures, relationships, data contracts, lineage, aggregation strategies, metric logic, refresh design, security attributes, and performance optimization.

Enterprise Access Model Security Governance

• Design and govern the enterprise Power BI access model using least-privilege principles and approved identity and entitlement standards.
• Define appropriate use of row-level security, object-level security, workspace roles, application audiences, build permissions, sharing controls, service principals, and self-service access.
• Establish reusable dynamic security patterns using governed identity, organizational hierarchy, role, population, geography, and entitlement data.

Enterprise Product Review Release Readiness

• Establish and apply technical review criteria for enterprise BI products, semantic models, shared components, and access models.
• Test row-level security, object-level security, workspace access, application audiences, build permissions, and entitlement rules using representative user roles before release.
• Use controlled development, versioning, comparison, deployment, and rollback practices to reduce production risk.
• Support production deployments, post-release monitoring, incident investigation, root-cause analysis, and stabilization.

Documentation, Governance Security

• Apply and reinforce standards for version control, peer review, modular development, testing, deployment, release management, monitoring, documentation, security, privacy, and data retention.
• Protect confidential and restricted information through approved access controls, data-handling practices, privacy requirements, security standards, and least-privilege principles.

AI-Enabled Engineering Responsible Analytics

• Use approved AI-enabled tools to accelerate DAX and SQL drafting, technical documentation, metadata analysis, test development, diagnostic investigation, quality review, and solution evaluation.
• Independently validate AI-assisted code, calculations, recommendations, interpretations, security logic, and documentation before use or release.

Education Experience

• Bachelors degree in Information Systems, Computer Science, Data Analytics, Engineering, Statistics, Mathematics, Business, or a related field; an equivalent combination of education and experience may be considered.
• 7+ years of progressively responsible experience developing, optimizing, supporting, or governing business intelligence and enterprise analytics solutions.
• Advanced experience with Power BI, DAX, Power Query, semantic models, reusable measures, calculation groups, security, deployment pipelines, and performance optimization.
• Experience designing and supporting enterprise Power BI access models, including row-level security, object-level security, dynamic security, workspace roles, application audiences, semantic-model permissions, build permissions, and governed self-service access.
• Experience using semantic-model development and diagnostic tools such as DAX Studio, Tabular Editor, ALM Toolkit, VertiPaq Analyzer, Power BI Performance Analyzer, XMLA endpoints, or comparable tools.
• Advanced SQL experience and demonstrated experience working with cloud-based analytical platforms, distributed databases, or large and complex enterprise datasets.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.