Top Analysis Reporting Jobs in Wilmington, NC

Build and scale resilient ingestion, catalog, and derived data pipelines powering core infrastructure datasets. Own data contracts, schema governance, quality gates, automated testing, observability, and pipeline reliability. Modernize legacy systems into scalable platform architecture, including a graph database layer. Partner with global engineering, data science, ML, intelligence, and trust teams to support matching, confidence scoring, and automated workflows.

Leads a multidisciplinary marketing analytics organization spanning data engineering, analytics engineering, visualization, and data science. Builds attribution, ROI, customer journey, predictive signal, data governance, and AI-ready information architecture systems. Partners with Sales, RevOps, Finance, PLG, and Data teams to improve capital allocation and growth decisions. Oversees executive dashboards, metric alignment, team capacity, and strategic analytics delivery.

Build and operate production pipelines for legal records from PACER, court systems, opinions, PDFs, scans, XML, and HTML. Develop LLM-assisted extraction workflows, validate data quality, optimize SQL, and support RAG and semantic search products. Manage AWS S3 and RDS systems within security guardrails while collaborating with engineering teams. The role requires strong Python and SQL skills, legal data experience, document extraction expertise, and autonomous problem-solving with large, messy datasets.

Architects, administers, secures, and optimizes enterprise database and infrastructure platforms supporting Navy readiness, training, and analytics systems. Leads database architecture, ETL/ELT pipelines, performance tuning, high availability, disaster recovery, virtualization, monitoring, cybersecurity compliance, vulnerability remediation, and access controls. Coordinates system changes, configuration management, interoperability, technical reporting, demonstrations, and training-material updates with Government, development, cybersecurity, and training stakeholders.

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.

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.

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.

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.