Top Senior Data & Analytics Jobs in Wilmington, NC

Lead data integration efforts: integrate and profile data from multiple sources, cleanse and enrich datasets, perform in-depth analysis, build automated data workflows, write and optimize complex SQL, create Tableau dashboards, produce ad hoc reports, translate insights for stakeholders, and manage UAT to ensure solutions meet business requirements.

Own the Finance & Operations data layer: ingest and model data from systems (NetSuite, Ramp, Pigment) into Snowflake/Omni, ensure data quality and metric governance, build dashboards and reports, collaborate with Finance/Ops stakeholders, and automate reconciliation and reporting workflows.

Manage and improve data processes and operational workflows: analyze large datasets, maintain data integrity, monitor KPIs, support automation and ETL, collaborate cross-functionally, and present findings to leadership.

Lead end-to-end FOIA data migration projects into RelativityOne, define and prioritize migration tooling, author requirements and runbooks, engage agency customers, ensure FedRAMP-compliant handling of DT1 data, and drive continuous improvement and product feedback.

Senior AWS Analytics Engineer. Posting contains no detailed responsibilities or qualifications beyond the job title.

Lead design and build of Microsoft Fabric data solutions and Power BI semantic models. Migrate Tableau reports to governed Power BI, develop Spark notebooks, implement medallion lakehouse patterns, optimize ETL/ELT and DAX, and support CI/CD and stakeholder validation.

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.

Design, develop, and maintain Snowflake-backed semantic models and Power BI reports; build SQL queries, functions, and stored procedures; use AI-assisted tooling (Claude, MCP) to accelerate BI development; manage work in Azure DevOps, version control with GitHub; ensure QA, documentation, stakeholder communication, and mentor fellow developers.