Business Analytics Specialist

Microsoft•Redmond, WA

15h•$106,400 - $222,600

About The Position

The Modern Analytics & Insights organization enables data-driven decision making across Microsoft’s Small, Medium, Enterprise & Channel (SME&C) business by delivering business intelligence, actionable insights, and analytical capabilities. This role supports the Corporate Accounts business, with a primary focus on the Corporate Accounts Intelligence Platform (CAIP) and Azure business intelligence and analytics. The Business Analytics Specialist owns and evolves BI and analytical capabilities that translate Corporate Accounts priorities into scalable reporting, semantic models, and analytical products. The role spans the analytics lifecycle: understanding business questions, defining metrics, designing semantic models, developing BI solutions, validating data, and driving adoption. Approximately 60% of the role focuses on Corporate Accounts BI, including CAIP and Azure analytics, and approximately 40% focuses on semantic models, data architecture, AI readiness, and self-service analytics enablement. The specialist builds and maintains trusted, actionable views of performance, including Azure performance, customer trends, pipeline and execution signals, and business outcomes. The role also contributes to SME&C’s broader data and analytics architecture by creating reusable semantic models, reducing fragmented reporting, improving data quality and performance, and preparing analytical assets for self-service and AI-enabled experiences.

Requirements

Experience building business intelligence solutions using Power BI, including dashboards, scorecards, executive reporting, and interactive analytical experiences.
Analytical and problem-solving ability to convert complex business questions into analytical solutions.
Experience working with sales, commercial, finance, operations, or customer performance data.
Ability to explain why performance is changing and what actions should be considered, beyond reporting results.
Experience translating business requirements into scalable analytical products rather than standalone reports.
Ability to own BI solutions from requirements through development, validation, deployment, and ongoing improvement.
Experience supporting sales operations, business operations, finance, strategy, performance management, or commercial organizations.
Understanding of business performance measurement, KPI design, pipeline and execution metrics, and executive reporting frameworks.
Experience analyzing customer, product, revenue, consumption, pipeline, or sales performance.
Ability to connect operational and sales indicators to broader business outcomes.
Hands-on experience designing and maintaining Power BI semantic models and enterprise analytical solutions.
Understanding of dimensional modeling, star schemas, relationships, measures, hierarchies, and semantic layer design.
Experience with DAX and SQL, and ability to independently investigate and validate data.
Experience building or optimizing solutions using Power BI and Microsoft Fabric.
Experience working with large or complex datasets and optimizing models for performance, usability, and scalability.
Understanding of data pipelines, data transformation, data quality, lineage, governance, and certification.
Experience consolidating fragmented semantic models or reporting solutions into reusable analytical foundations.
Understanding of how semantic models, metadata, business definitions, and data quality enable Copilot, natural-language analytics, and AI-agent scenarios.
Ability to explain complex analytical findings in simple business terms and create executive-ready scorecards, presentations, and analytical narratives.
Ability to distinguish between reporting a metric and explaining its business drivers.
Ability to communicate effectively with technical teams and business stakeholders.
Proven ability to work across business, analytics, engineering, and operations organizations.
Ability to independently manage BI products and analytical workstreams from definition through delivery.
Prioritization and execution skills to balance business urgency with long-term architectural quality.
Comfort working in an environment where business priorities and analytical requirements evolve rapidly.
Demonstrated focus on quality, accuracy, scalability, and user experience.
Master’s degree in a listed relevant field and 3+ years of experience in data analysis and reporting, business intelligence, or business and financial analysis; or bachelor’s degree in a listed relevant field and 4+ years of such experience; or equivalent experience.

Nice To Haves

Experience with cloud, Azure, enterprise software, or technology-industry business models.
Master’s degree in a listed relevant field and 6+ years of experience in data analysis and reporting, business intelligence, or business and financial analysis; or bachelor’s degree in a listed relevant field and 8+ years of such experience; or equivalent experience.

Responsibilities

Serve as a primary analytics partner for the Corporate Accounts CAIP business, understanding its priorities, performance drivers, customer segments, sales motions, and execution model.
Own and evolve BI experiences supporting Corporate Accounts CAIP and Azure analytics.
Develop and maintain executive scorecards, dashboards, KPIs, business review views, and analytical products.
Develop analytical experiences covering Azure performance, growth trends, customer performance, pipeline and execution signals, and business opportunities or risks.
Partner with business leaders, Sales Excellence, Finance, Strategy, and Operations to define reporting requirements, metrics, analytical priorities, and success measures.
Translate business requirements into scalable BI solutions rather than one-off reports or analyses.
Identify trends, performance drivers, risks, and opportunities and communicate them through clear analytical narratives.
Ensure CAIP and related reporting experiences use consistent definitions and reconcile across executive, field, and operational views.
Continuously improve the usability, performance, and relevance of Corporate Accounts BI.
Design, develop, and maintain semantic models and analytical data products supporting Corporate Accounts, CAIP, and Azure reporting.
Build and optimize Power BI and Microsoft Fabric semantic models for BI, self-service analytics, and AI-enabled experiences.
Translate business concepts into dimensions, measures, hierarchies, relationships, and reusable analytical logic.
Establish consistent definitions for key metrics and implement business logic consistently across reporting experiences.
Partner with data engineering teams to improve source data quality, model scalability, refresh reliability, governance, and platform performance.
Consolidate semantic models, rationalize overlapping reporting assets, reduce technical debt, and simplify the BI architecture.
Design analytical assets for natural-language querying, Copilot-enabled experiences, agentic analytics, and other AI-driven scenarios.
Ensure semantic models include definitions, metadata, relationships, descriptions, and business context for human and AI consumption.
Support certification of enterprise data assets and semantic models so they are trusted, governed, documented, and discoverable.
Monitor and improve model performance, scalability, usability, and reliability.
Analyze Corporate Accounts performance across multiple data sources to identify customer, product, sales, and execution trends.
Investigate performance changes and determine underlying business drivers.
Conduct deeper analysis of potential risks, opportunities, and areas requiring further investigation.
Evaluate the impact of business initiatives, investments, programs, and execution changes.
Develop repeatable analytical approaches and convert analysis into actionable recommendations.
Connect detailed analytical findings to broader Corporate Accounts and Azure business outcomes.
Build relationships across Corporate Accounts leadership, Finance, Strategy, Sales Excellence, Operations, Engineering, and Analytics organizations.
Work with stakeholders to understand decisions they need to make and the analytical capabilities required to support them.
Challenge unclear or inconsistent metric definitions and help establish common analytical standards.
Translate business questions into data requirements, semantic model requirements, KPIs, and analytical experiences.
Communicate analytical findings and technical concepts to business and technical audiences, and influence decisions with fact-based recommendations.
Promote consistent analytics practices, including metric governance, reporting standards, documentation, testing, and quality assurance.
Eliminate duplicated or low-value reporting and increase reuse of trusted semantic models and common analytical components.
Automate recurring analytical processes and reduce manual reporting where practical.
Evaluate Microsoft Fabric, Power BI, Copilot, and AI capabilities and apply them where they improve the analytics experience.
Support SME&C’s AI-first analytics strategy by preparing Corporate Accounts data and semantic models for safe use in traditional BI and emerging AI experiences.