Top Analysis Reporting Jobs in Hampton, VA

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy; delivers executive dashboards, KPI scorecards, operational reporting, semantic models, and self-service BI. Establishes data governance and metric standards, ensures data quality, partners with Engineering, Product, Finance, Operations, and executives, and translates business questions into actionable analytical solutions. Mentors analytics talent and drives prioritization, adoption, and measurable business outcomes.

Designs and maintains scalable data architecture, Snowflake warehouses, ETL/ELT pipelines, dimensional data models, and governance processes. Partners with business stakeholders to deliver insights for pricing, inventory, customer segmentation, and marketing optimization. Builds reliable analytics datasets and dashboards, integrates data tools, monitors data quality, and ensures compliance within the regulated cannabis industry.

Designs and builds production data systems, pipelines, database schemas, analytical models, and internal platforms. Responsibilities include writing tested code, optimizing queries and storage, controlling infrastructure costs, enforcing CI/CD, and implementing data testing, monitoring, and alerting. The role also develops AI and LLM-backed data use cases, including retrieval pipelines, embeddings, vector storage, evaluation harnesses, and agentic workflows.

Own and scale client-facing data transformation pipelines for financial and operational data. Build reliable analytical models, data integrity tests, and integrations across diverse sources. Partner with Customer Success and Engineering to troubleshoot data issues, optimize critical pipelines, establish engineering standards, and improve developer experience. Use dbt, SQL, Python, BigQuery, and AI-enabled workflows to deliver performant, well-documented FP&A data products while mentoring teammates and contributing to hiring and onboarding.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

Own Marketing’s reporting and analytics layer by building executive dashboards, defining KPIs, modeling data across GTM systems, and establishing governance and trusted sources of truth. Partner cross-functionally to measure funnel performance, attribution, campaigns, pipeline, and ROI. Help evaluate and develop AI-powered analytics, conversational reporting, automated insights, and intelligent visualization while translating complex data into actionable recommendations for leadership.

Leads enterprise strategy, architecture, delivery, governance, and operations across data, analytics, information management, automation, AI, and GenAI. Drives transformation toward governed data foundations, reusable data products, data marketplaces, self-service analytics, and responsible AI. Oversees platforms, pipelines, dashboards, automation initiatives, budgets, vendors, and senior technical teams while partnering with business, Legal, Compliance, Quality, and Security. Builds training, adoption, stewardship, and change-management programs across a global life sciences organization.

Serves as a strategic analytics partner to Marketing, owning funnel, attribution, ROI, account scoring, experimentation, and pipeline analytics. Builds scalable datasets, dashboards, and quality controls while connecting customer, campaign, product usage, CRM, and revenue data. Delivers executive-ready reporting, QBR insights, and recommendations that improve conversion, marketing investment effectiveness, account-based marketing, product adoption, and pipeline growth.

Investigate offline and direct mail channel performance, attribution, vendor data, and measurement methodologies. Build response, lift, allocation, and regression models; manage direct mail testing data pulls and mail merges; create KPI dashboards; and communicate actionable recommendations to marketing stakeholders. The role requires proactively identifying opportunities, validating data and vendor claims, and translating complex analytical findings into business decisions.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.