Senior Power BI & Data Analyst

Responsibilities

The Senior Power BI & Data Analyst will design and maintain enterprise-level dashboards while applying statistical modeling to drive strategic business decisions. This role involves partnering with executive stakeholders to provide actionable insights across sales, finance, and supply chain operations.

Requirements

Candidates must possess a bachelor's degree in a quantitative field and at least 7 years of experience in analytics or BI. Proficiency in Power BI, advanced SQL, and statistical programming languages like Python or R is required.

Skills

• Power BI
• DAX
• SQL
• Python
• R
• Statistical Modeling
• Predictive Analytics
• Data Governance
• ETL/ELT
• Data Warehousing
• Business Intelligence
• Financial Analysis
• Forecasting
• Data Visualization
• Regression Analysis
• Semantic Modeling

About this role

Senior Power BI & Data Analyst
Statistical Modeling, Advanced Analytics & Business Intelligence
Industry: Technology, Telecommunications, Digital Infrastructure & Micro-Energy Distribution
Department: Data Analytics / Business Intelligence
Reports To: VP of Data Analytics
Position Level: Senior Individual Contributor
Employment Type: Full-Time
Position Summary
The Senior Power BI & Data Analyst transforms complex commercial, operational and financial data into actionable insights that support strategic decisions, revenue growth, profitability and operational efficiency. This role combines enterprise Power BI development with statistical modeling, predictive analytics, forecasting, data governance and executive-level business partnering.
Key Responsibilities
Business Intelligence & Power BI
Design and maintain enterprise Power BI dashboards, reports and semantic models.
Build advanced DAX measures, Power Query transformations and dimensional models.
Integrate ERP, CRM, finance and supply chain data; implement row-level security and refresh monitoring.
Optimize report performance, standardize KPI definitions and enable governed self-service analytics.
Statistical Modeling & Advanced Analytics
Apply regression, hypothesis testing, multivariate analysis, segmentation and clustering.
Build time-series and predictive models for revenue, customer demand, inventory and profitability.
Use Python or R to evaluate assumptions, confidence intervals, model accuracy and limitations.
Conduct sensitivity, scenario and what-if analyses and translate results into business actions.
Sales, Revenue & Commercial Analytics
Analyze direct and indirect channel performance, bookings, pipeline, gross margin and retention.
Develop sales forecasts, customer profitability and lifetime-value models.
Evaluate pricing elasticity, discounting, margin leakage and cross-sell opportunities.
Procurement, Inventory & Supply Chain
Model inventory demand, turnover, stockouts, obsolete stock and working capital.
Develop supplier scorecards, purchasing trends and fulfillment performance analysis.
Identify opportunities to improve procurement efficiency and inventory positioning.
Financial & Profitability Analytics
Analyze revenue, gross profit, expenses and budget-to-actual variances.
Develop profitability reporting by customer, product, supplier, channel and business unit.
Partner with Finance on reconciliation, forecasts and scenario planning.
Data Quality, Engineering & Governance
Write complex SQL and support ETL/ELT, data warehouse and lakehouse integrations.
Implement validation, reconciliation, documentation and master-data quality controls.
Collaborate with IT on reliable, secure and scalable data architecture.
Executive Decision Support & Automation
Present analytical findings, risks and recommendations to executive stakeholders.
Automate repetitive reporting and build reusable models and templates.
Mentor analysts and business users on Power BI and analytical best practices.
Required Qualifications
Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, Finance, Economics or related quantitative field; master's preferred. 7+ years in analytics or BI, including 5+ years of advanced Power BI and 3+ years of statistical modeling, forecasting or predictive analytics. Experience with large datasets, executive reporting and ERP/CRM systems required. Distribution, telecommunications or digital infrastructure experience preferred.
Required Technical Competencies
Advanced Power BI, DAX, Power Query (M), semantic modeling, star schemas, security and performance tuning.
Advanced SQL, joins, CTEs, window functions and query optimization.
Python or R with statistical libraries such as pandas, NumPy, SciPy, statsmodels or scikit-learn.
Regression, hypothesis testing, time-series forecasting, clustering, model validation and statistical communication.
Advanced Excel, ETL/ELT, relational databases and data warehousing.
Preferred Technologies
Microsoft Fabric, Azure SQL, Azure Data Factory and related Azure services.
Snowflake, Databricks, Dynamics 365, Salesforce, SAP or Oracle.
Git, machine learning workflows and AI-assisted analytics.
Professional Competencies
Business and financial acumen; analytical judgment and critical thinking.
Executive communication, stakeholder collaboration and concise data storytelling.
Attention to data integrity, ownership, prioritization and mentoring.
Key Performance Indicators
Performance Area

Illustrative Target

Reporting Delivery

95%+ on-time scheduled reports

Data Accuracy

99%+ accuracy of validated critical metrics

Dashboard Performance

95%+ meet agreed performance standards

Forecast Accuracy

Meet use-case-specific accuracy thresholds

Reporting Automation

25-40% reduction in manual reporting effort

Analytics Adoption

Growth in active dashboard usage

Project Delivery

90%+ completed to agreed schedule

Stakeholder Satisfaction

90%+ positive satisfaction

Model Quality

Meet defined validation and stability criteria

Targets are illustrative and should be finalized against organizational baselines and priorities.
Expected Deliverables
Executive performance dashboards and standardized KPI reporting.
Sales, revenue, customer demand and inventory forecasting models.
Customer, product, channel and supplier profitability analytics.
Pricing and margin optimization analysis.
Documented data definitions, statistical methods, model validations and automated reporting solutions.
Success Profile & Position Impact
The successful candidate goes beyond historical reporting to explain performance drivers, anticipate future outcomes and recommend measurable improvements in growth, margins, working capital and operational effectiveness. The position helps establish a reliable, scalable, data-driven decision-making culture.

About Network Wireless Solutions

Telecommunications · 51-200 employees · headquartered in Greensboro, NC · founded 2012