Top Remote Data & Analytics Jobs in Wilmington, NC

Lead data architecture for NAVSUP OIS, including database design, data modeling, warehouse strategy, ETL/ELT pipelines, migration, security, retention, backup, recovery, and performance optimization. Coordinate cloud and containerized environments, guide data engineers and DBAs, and support modernization from Oracle to cloud and analytical platforms. The role also provides technical leadership, architecture planning, integration, risk assessment, and policy development for mission-critical systems.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.

Analyzes healthcare claims, provider, pharmacy, and enrollment data to identify trends, improve data quality, optimize workflows, reduce costs, and support business decisions. Translates business needs into requirements, develops complex SQL queries, validates data, recommends process improvements, coordinates projects, and serves as a liaison among operations, research and development, IT, and external partners. Also mentors team members and communicates technical findings to nontechnical stakeholders.

Owns and codifies business definitions and calculation methods for legal spend analytics, audits legacy Excel/PowerPoint artifacts, validates analyses (SQL and AI), supports reporting and storytelling for senior law department and C-suite audiences, and helps migrate analyses into modern analytics tooling.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Develops and manages enterprise business intelligence products, including semantic models, governed definitions, metadata, dashboards, and AI-assisted analytics capabilities. Translates complex business needs into measurable analytic solutions, advises stakeholders, supports adoption and training, and manages product lifecycle, quality, performance, and business impact. Partners with product managers and business leaders to prioritize work, manage risks, communicate value, and guide less experienced team members.

Analyze web, journey, survey, and marketing data to uncover actionable insights for enterprise clients. Translate technical findings into business recommendations, test-and-learn plans, dashboards, reports, and presentations. Collaborate with account teams, ensure data quality and statistical rigor, investigate anomalies, and support client questions. The role requires expertise in analytics platforms, data visualization, spreadsheets, SEO, and client-facing data storytelling in a fast-paced SaaS environment.

Lead the analytics function by building Power BI and Superset dashboards, conducting deep-dive analyses, and applying AI and NLP tools to generate insights. Own reporting data observability, SQL and database performance, production support, capacity planning, and platform reliability at scale. Collaborate with customers and cross-functional teams on analytics solutions and roadmap development while building and mentoring a high-performing analytics team.

Leads enterprise analytical modeling and semantic architecture, establishes standards for testing, documentation, governance, lineage, observability, and access, and develops reusable governed data products. Partners across Product, Engineering, Finance, Clinical, Research, Marketing, and AI teams; guides architecture reviews, data quality ownership, semantic layer design, and governance adoption. Mentors engineers and drives modernization of analytical environments.