Top Senior Business Intelligence Jobs in Hampton, VA

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.

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.

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.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.

Validate and QA data across UI and API sources, investigate issues, manage taxonomy mismatches, compile non-automated reports, and update/maintain dashboards (Power BI/Tableau). Collaborate with Business Strategy, Investment, and Analytics teams to resolve data and KPI anomalies.

Design, develop, and deploy Power BI reporting and analytics on Snowflake. Migrate OBIEE reports to Power BI, build data models and ETL/ELT pipelines, write DAX and SQL, optimize report performance, ensure data quality, and support stakeholders with documentation and ongoing support.

Design, build, and maintain enterprise Power BI dashboards and data models. Integrate multiple data sources, write DAX, ensure data quality and performance, support stakeholders with requirements, documentation, governance, and ad hoc analytics to enable operational and executive decision-making.

Lead design, development, and maintenance of BI solutions (dashboards, reports, datasets). Partner with product, actuarial, underwriting to source and validate data. Automate reporting, perform audits/reconciliations, communicate findings to stakeholders, and mentor analysts. Act as Power BI SME and apply AI tools to accelerate development, code generation, automation, and QA.

Own and build Power BI reports and client-facing intelligence products within Microsoft Fabric. Develop DAX measures, campaign pacing and budget alerting, monitor contact data health and data delivery pipelines, transition vendor-built platforms in-house, and partner with IT/Data Engineering and cross-functional teams to ensure reliable, actionable reporting for Digital leadership and clients.

Design and implement scalable data platforms, build ETL/ELT pipelines, integrate multiple data sources, define KPIs, create dashboards and executive reports, ensure data quality/governance, and collaborate with stakeholders to optimize BI capabilities.

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.

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.

Design, develop, and maintain BI dashboards, self-service reporting, and predictive analytics for a cloud-based federal case management program. Translate business requirements into technical designs, implement SQL/data transformations, ensure governance and compliance, support AI/ML capabilities, and drive adoption and performance of analytics solutions.

Lead analytics and BI for Digital Product Operations: define product and adoption metrics, build dashboards, ensure data governance and quality, measure ProdOps effectiveness, coach PM/POs, diagnose adoption gaps, and drive interventions that improve product planning and delivery.

Lead Tilt's Business Intelligence function end-to-end: manage a distributed BI team, own reporting data models and semantic layer, build and maintain a metric-and-metadata library with reference SQL, review dbt work and hold quality through code review, prioritize stakeholder requests, and grow team technical and business fluency.

Own and maintain KPI reporting pipelines and business logic, ensure data quality, diagnose KPI changes, perform deep-dive analyses, build dashboards and visualizations, architect data models and curated reporting zones, and partner with Data Engineering and product/marketing stakeholders to enable self-service analytics.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.

Lead product analytics efforts to define KPIs, build measurement frameworks, analyze customer behavior, and generate insights that influence product and engineering decisions. Partner with Product, Engineering, and Data teams to design event tracking, run experiments, quantify opportunity sizes, and communicate recommendations through clear narratives and visualizations to drive product adoption, retention, and business outcomes.

Lead ownership of BI reporting infrastructure: build and standardize dashboards, extract insights from messy third‑party data, partner with marketing teams to drive performance optimization and deliver proactive retrospective analyses that influence business decisions.