Top Analysis Reporting Jobs in Wilmington, NC

Leads digital and marketing analytics for customer acquisition across multiple lending brands. Owns performance reporting, measurement frameworks, data governance, attribution and marketing effectiveness models, funnel analytics, experimentation, dashboards, and executive insights. Partners with Marketing, Risk, Finance, Operations, Technology, Engineering, and Data teams to optimize conversion, ROI, customer journeys, and data infrastructure. Requires advanced SQL, web analytics, statistical analysis, experimentation, and marketing measurement expertise.

Lead architecture and hands-on development of cloud-native data platforms, distributed pipelines, lakehouse systems, backend services, APIs, and observability frameworks. Establish data engineering standards, governance, CI/CD practices, and reliable real-time analytics foundations supporting AI and machine learning. Mentor engineering teams, conduct design and code reviews, and coordinate technical execution across platform, security, and product stakeholders.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

Develop and maintain reports, dashboards, KPIs, and executive insights using SQL, Power BI, and other BI tools. Reconcile operational and financial data, investigate anomalies, ensure reporting quality, and document data models, metadata, governance, and reporting inventories. The role also performs advanced data manipulation, visualization, data storytelling, and analytical recommendations. Fraud and disputes domain knowledge is preferred.

Lead design, build, test, and maintain scalable cloud data platforms and pipelines (ETL/ELT, batch and streaming). Ensure data quality, governance, security, CI/CD deployment, performance tuning, migration/archival, and mentor data engineering teams to support analytics and AI/ML use cases for a federal modernization program.

Troubleshoot student information system integrations, configure imports, write SQL and extract scripts, perform database updates, validate data quality, investigate discrepancies, and resolve integration errors. The role also supports customers with ETL guidance and status updates while collaborating with product, engineering, and cross-functional teams.

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.

Design, build, and maintain Keboola-based data pipelines integrating multiple business systems to deliver accurate, scalable data for supply chain, logistics, and transportation analytics; collaborate with analysts and engineers; support documentation, governance, and pipeline automation.

Leads Planning Analytics and Rapid Analytics teams supporting segmentation, quota planning, territory models, investment optimization, and executive decision-making. Builds rapid, hypothesis-driven analyses and translates complex data into actionable recommendations. Partners with Engineering to develop scalable data foundations, semantic models, governance, self-service analytics, and AI-ready capabilities using Power BI, Fabric, and SQL. Oversees talent development, stakeholder alignment, and strategic analytics consulting across business functions.

Build and steward Netflix advertising quality-of-experience data, from device telemetry and instrumentation through data pipelines and dashboards. Collaborate with product engineering, data engineering, and data science teams to measure user-perceived performance, improve data quality, document user flows, and establish monitoring and measurement best practices. The role requires strong SQL and Python skills, technical communication, stakeholder management, and comfort working independently in an ambiguous environment.

Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.