Top Remote Data & Analytics Jobs in Wilmington, NC

Lead and manage data engineering teams to design, build, and maintain high-quality data pipelines. Oversee automation, performance scripting, data modeling, database optimization, and quality-control processes. Collaborate with product, engineering, and operations to deliver data-driven features and support SEC-related data needs and AI/LLM integrations.

The Business Analyst will assess operations, analyze data, strategize improvements, and collaborate with clients while supporting a consulting team.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

As a Salesforce Technical Architect focused on Data & AI, you'll design and implement solutions using Salesforce Data 360, oversee technical projects, collaborate with various stakeholders, and mentor junior staff to drive AI innovations.

Trace3 seeks enthusiastic individuals for its Data Intelligence Team. The role focuses on innovative technology solutions and consulting services, fostering a collaborative and dynamic work environment.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Develop and lead healthcare analytics and BI solutions for HIS products: design, code, and deliver enterprise-scale applications and dashboards, work with AWS data services and BI tools, support product development and troubleshoot reporting issues for global customers.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Assist in collecting, cleansing, and analyzing datasets to produce actionable insights, reports, and dashboards for informed business decisions.