Top Senior Business Intelligence Jobs in Raleigh, NC

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

Design and implement BI solutions and data pipelines, apply advanced analytics to derive insights, build client relationships, lead and mentor teams, and improve data quality and visualization using tools like Oracle BI, QlikView, and Spotfire.

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.

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.

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.

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

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

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.

The Market & Business Intelligence Manager will lead analytics strategies, manage a team of business analysts, and provide insights to support firm strategy and decision-making.

Design, build, and maintain scalable AWS data pipelines, data lakes, and warehouses; develop ETL/ELT processes; create and manage AWS QuickSight dashboards (including RLS, embedding, Topics/Spaces, and QuickSight Q); ensure data quality, governance, security; optimize performance; collaborate with stakeholders and support production reporting.

Analyze large healthcare datasets and develop complex SQL queries using Azure Synapse/Databricks. Build Power BI reports, produce monthly reconciliations and ad-hoc analyses in Excel/PowerPoint, support payments to value-based specialists, evaluate and expand value-based programs, automate processes with Power Automate/Power Apps, and communicate findings to senior leadership while spearheading new technologies.

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.

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.

Ensure integrity and governance of reporting databases; develop automation frameworks and ETL processes; prepare data for BI; conduct code and periodic reviews; create data policies and documentation; collaborate with stakeholders to enforce data management practices; perform data, gap, and root-cause analysis; maintain performance and adopt new technologies.

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.

Own end-to-end marketing and business intelligence: build automated dashboards (Domo), query large datasets (SQL/Snowflake), report subscription funnel economics, analyze channel performance and A/B tests, troubleshoot data anomalies, and partner with leadership to set KPIs and prioritize analytics work.

Lead cross-functional analytics to inform clinical and operational decisions: build Tableau dashboards, create dbt analytical models, analyze large healthcare datasets (claims, EHR, HIE) with SQL, respond to ad-hoc requests via JIRA, and collaborate with product and engineering to improve data capabilities.

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.

Support and develop BI applications for a client financial platform across environments. Build reports, analytics, and budgeting solutions (TM1), develop/tune Oracle SQL/PLSQL, deploy BI tooling, support UIs (low-code), follow Agile practices, and collaborate on integrations, security hardening, and operations.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

The Senior BI Analytics Engineer will design and deliver data models for analytics, ensuring data quality, and collaborating across teams to enhance AI-driven reporting and querying capabilities.

Hands-on technical lead designing and delivering scalable, secure Azure-based BI and analytics solutions. Own end-to-end Power BI architecture, mentor engineers, guide implementations, optimize performance, and advise clients on governance, deployment, and AI-augmented analytics. Drive discovery, backlog priorities, cross-team alignment, reusable assets, and consulting pursuits.

Design, maintain, and automate GTM business data models, ensure data quality and observability, build BI-as-code pipelines (CI/CD, Git), create visualizations, and partner with Sales, Marketing, Finance, and Product to enable reliable reporting, analytics, and AI capabilities.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.