Top Senior Data & Analytics Jobs in Wilmington, NC

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

Embed with the CRO to deliver GTM analytics and insights: write SQL and dbt models, build Looker and Salesforce dashboards, define and track revenue KPIs, forecast and model revenue, partner with GTM leaders and Data Engineering, lead analytics projects, and translate complex data into executive-ready recommendations to drive upsell and new-business growth.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Design and evolve enterprise data architecture and models (conceptual, logical, physical). Lead LDM/PDM development, run JAD sessions, apply naming standards, use data profiling and modeling tools, review models with SMEs, coordinate multi-stream teams and third parties, and communicate architecture to senior stakeholders.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Lead development and maintenance of actuarial data marts, extracts, reports, validations and audits. Drive requirements, technical specs, automations, and financial analyses; mentor staff and coordinate with vendors and business partners to ensure accurate, auditable financial data.

Design and implement scalable data pipelines and orchestration on GCP to support AI/ML-driven mail intelligence. Build stream and batch processing, ensure data governance and quality, optimize workflows, create visualizations, and collaborate with US cross-functional teams to align technical strategy and recover from failures.

Design, build, and maintain scalable cloud-native data pipelines, microservices, and AI-driven orchestration. Develop Python APIs (Flask/FastAPI), implement advanced SQL transformations (BigQuery), integrate LLMs/agents for automated workflows, and collaborate with Data Science and Product to deliver production-grade, observable, and secure AI-enabled data solutions.