Top Analysis Reporting Jobs in Wilmington, NC

Leads business analysis, advanced analytics, KPI development, data modeling, reporting automation, and AI/ML initiatives supporting global data-center construction and operational excellence. Builds datasets, dashboards, performance metrics, forecasts, and scenario models; translates complex findings for executives; aligns technology solutions with business needs; and promotes data governance, documentation, process improvement, and analytics maturity across cross-functional teams.

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.

Supports DIRECTV FOR BUSINESS through KPI analytics, financial analysis, customer segmentation, and process improvement initiatives. The intern analyzes performance drivers, commitments, projects, and customer experience impacts; synthesizes insights into data stories; documents processes; and presents findings to leaders. The role involves cross-functional virtual collaboration and requires proficiency in Excel, PowerPoint, Python, SQL, Power BI, and data visualization.

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.

Lead the architecture and implementation of enterprise-scale GCP data ecosystems, including PB-scale platforms and AWS-to-GCP migrations. Establish data platform roadmaps, self-service architectures, governance, security, quality, and Infrastructure as Code standards. Architect solutions using GCP data, analytics, AI, streaming, and containerization technologies. Lead cross-functional engineering teams, mentor staff, advise executives, manage technical risks, and communicate the business value of data initiatives.

Manages the enterprise Data Governance and Analytics Center of Excellence, leading staff, governance initiatives, analytics strategy, maturity modeling, budgets, vendors, and planning. Coordinates data quality, stewardship, privacy, acquisition, and release programs while partnering with data scientists, engineers, technology governance teams, and business stakeholders. Develops executive presentations, aligns enterprise definitions and algorithms, establishes standards, and ensures analytics projects and business cases meet organizational objectives and deadlines.

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.

Design and lead scalable data engineering solutions across Databricks and Microsoft Azure. Define enterprise data modeling standards, architect pipelines and integrations, establish engineering best practices, troubleshoot complex platform issues, and guide modernization and cloud migration initiatives. Provide technical leadership and mentorship while ensuring data platforms meet security, quality, governance, reliability, performance, and maintainability standards.