Top Senior Business Intelligence Jobs in Greensboro, NC

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Act as a strategic partner to Revenue Operations by analyzing performance, building executive dashboards and reports, improving CRM data quality and governance, supporting forecasting and pipeline management, and designing scalable processes and automations to increase efficiency and revenue visibility.

Lead data product strategy and governance for customer-facing reporting within Managed Services. Own reporting product roadmap, data quality, standards, delivery platforms (Redwood Insights, BI, Snowflake, Excel), implementation readiness, and cross-functional alignment to scale trusted, automated customer analytics and reduce manual reporting.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Own and operate the Microsoft Fabric and Power BI platform end-to-end: administer tenants, capacities, OneLake, and governance; build secure data integration pipelines and access layers for BI and AI agents; automate CI/CD and platform operations; enforce security and data governance; and translate business requirements into technical designs while liaising between IT, security, and business stakeholders.

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Lead BI reporting and advanced analytics to optimize marketing campaigns and ROI. Build dashboards, manage multi-source data, ensure data governance, provide actionable insights, mentor juniors, and partner with cross-functional teams to guide strategy.

Lead BI partner for product teams to design and maintain scalable data pipelines, dbt transformations, data marts, and observability. Translate business needs into analytical frameworks, support A/B testing and ML feature engineering, collaborate on data governance, and champion CI/CD and best practices for analytics engineering.

Design and deliver BI reports, dashboards, scorecards and analytic solutions for Medical Economics. Partner with business, actuarial, and technical teams to gather requirements, define business rules, manage BI development lifecycle, investigate trends, maintain knowledge base, and support analytics projects to inform cost and performance decisions.

Design, develop, and publish advanced interactive Power BI reports and dashboards; define data structures and ETL needs; build analytics models using Microsoft BI stack (Power BI, SSAS/AAS, dataflows); use DAX and SQL to implement complex logic; collaborate with data engineering and business partners; mentor junior developers and performance-tune reports.

Builds and manages ETL processes and data pipelines in Azure Databricks using PySpark. Integrates data from multiple sources, tunes Spark and SQL for performance, troubleshoots pipeline failures, automates manual processes, and supports reporting and analytics to inform business decisions.

Senior BI Engineer develops scalable data pipelines and visualizations to support market and corporate leaders. Responsibilities include analyzing complex datasets, building Databricks pipelines, creating Power BI reports, mentoring teammates in low-code (Power Apps), and delivering data-driven insights to senior leadership to improve provider contract performance and related processes.

Develop, maintain, and optimize BI reports and dashboards (primarily Power BI) by querying large data sets with SQL, translating business requirements into technical specs, creating wireframes, conducting demos and testing, troubleshooting data quality, and delivering actionable visualizations and insights to stakeholders.

Lead a team of BI engineers to design, govern, and deliver enterprise BI platforms, dashboards, and self-service analytics. Ensure data accuracy, KPI standardization, platform administration (Power BI/Tableau), semantic modeling, and stakeholder engagement while enforcing governance, driving adoption, and mentoring staff.

Lead cross-functional analytics and reporting efforts: build and maintain dashboards and automated reports, extract/clean large datasets from ERP/eCommerce/operational systems, define KPI governance, support forecasting and budgeting, improve data pipelines, and deliver actionable insights to inform strategic and operational decisions.

Embed as the primary analytics partner on a digital product team to define KPIs, own measurement plans, build PowerBI dashboards, analyze member product behavior and funnels, design and evaluate A/B tests, write SQL/Python for analyses, and translate findings into actionable recommendations for product leaders and senior stakeholders.

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.

Collect and analyze competitive intelligence and conduct due diligence and investigations on investment candidates and related entities. Design data collection methods, use research, network analysis and AI/automation tools to produce high-quality reports and actionable recommendations for senior stakeholders, and improve workflow productivity.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.