Top Analysis Reporting Jobs in Wilmington, NC

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.

Lead modernization of Navy fleet training analytics by transitioning FLTMPS reporting to Tableau within the Jupiter cloud data environment. Analyze training readiness, compliance, workflows, and capability maturity; develop dashboards using Tableau, Qlik Sense, and Databricks; establish authoritative enterprise reporting datasets; and oversee training material development, sustainment, and delivery. Coordinate government, fleet, and contractor requirements while supporting FTM/FLTMPS processes.

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.

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.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.