Top Senior Data & Analytics Jobs in Wilmington, NC

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.

Develops scalable data models, dashboards, reports, and analytical solutions that support business decisions. Partners with stakeholders to translate requirements, ensures data accuracy and usability, provides technical guidance to end users, documents architectures and processes, and communicates findings to technical and non-technical audiences. The role requires advanced Spotfire, SQL, and business intelligence experience, plus familiarity with modern data platforms and AI-assisted development tools.

The Insights Lead Analyst will develop analytics strategies, connect data for insights, and deliver actionable recommendations to clients, enhancing marketing decisions based on data analysis.

Leads a client’s migration from SQL Server, SSIS, and SSRS to Snowflake and Sigma while maintaining legacy reporting operations. Designs data models, ETL pipelines, reports, dashboards, source-to-target mappings, and migration plans; validates reporting parity and coordinates phased cutovers. The role also provides client-facing technical leadership, troubleshooting, documentation, peer reviews, and ongoing support for banking data and reporting systems.

Design, develop, and operate large-scale data ingestion, transformation, enrichment, and processing pipelines across cloud, hybrid, and on-premises environments. Build distributed services using Java, Python, and Kafka; optimize data models and platform performance; deploy applications on Kubernetes; support infrastructure automation and CI/CD; troubleshoot production systems; and collaborate with customers and solution architects on implementations.

Own regulatory analytics and reporting by building audit-ready datasets, dashboards, data models, pipelines, governance controls, and compliance automations. Analyze complex financial and compliance data, support audits and risk assessments, monitor data quality, and translate regulatory requirements into reliable reporting solutions using Python, SQL, dbt, and Airflow. Partner with engineering, analysts, compliance teams, and leadership to deliver actionable insights and improve regulatory processes.

Lead the architecture, development, and optimization of Snowflake and enterprise data platforms. Design scalable ETL/ELT pipelines, dimensional data models, and medallion architectures while establishing engineering standards for testing, deployment, monitoring, security, and data quality. Partner with stakeholders on technical roadmaps, mentor engineers and analysts, conduct design and code reviews, modernize legacy pipelines, and deliver reliable, reusable data solutions.

Administer Informatica and MuleSoft data governance and quality platforms in AWS GovCloud production environments. Responsibilities include installation, integration, security, performance tuning, backup and recovery, high availability, monitoring, testing, RMF/ATO support, documentation, incident response, and technical mentoring. The role integrates data catalogs and quality services with Yellowbrick, PowerCenter, and ETL systems while maintaining secure, repeatable configurations and operational readiness.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

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.