Top Senior Analysis Reporting Jobs in Wilmington, NC

Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.

Designs, implements, and maintains data pipelines, integration solutions, and data architecture using Snowflake and related data engineering tools. Analyzes insurance industry challenges, develops solutions, supports consulting engagements, presents recommendations, and collaborates with client stakeholders. The role also requires data modeling, ETL, cloud platforms, data governance, troubleshooting, and the ability to manage multiple initiatives while traveling up to 50%.

Leads a team of data engineers responsible for building and scaling Niche’s data platform. Oversees data pipelines, warehouse layers, platform reliability, data quality, monitoring, and engineering best practices. Manages roadmap execution, Agile rituals, cross-functional collaboration, hiring, mentoring, and career development. The role also drives process improvements, operational excellence, scalability, and delivery of secure, observable data solutions supporting analytics, reporting, content, and operational systems.

Creates, analyzes, edits, and maintains GIS data supporting fiber and HFC network planning, design, construction, and regulatory map updates. Uses ArcGIS and ArcFM to manage geodatabases, spatial datasets, parcel data, route assets, and network schematics. Conducts map research, interprets technical records, supports GIS projects, develops mapping standards, and responds to internal requests. Collaborates with legal, market expansion, engineering, construction, and design teams while ensuring geospatial data quality and alignment with GIS best practices.

Leads the architecture, development, and maintenance of scalable batch and real-time data pipelines, cloud data platforms, ETL/ELT workflows, and ML data infrastructure. Establishes standards for data quality, observability, lineage, governance, security, and modeling. Partners with data scientists, engineers, DevOps, and business stakeholders; evaluates technologies, drives technical initiatives, mentors engineers, and supports production-grade APIs and machine learning pipelines.

Own end-to-end data architecture, including ingestion, ETL, transformation, extracts, reporting, and dashboards. Lead DevOps and infrastructure for AI engineering systems, establish platform standards, and build reliable production infrastructure. Write and ship code, mentor engineers, and hire and lead a growing data and platform team. Partner with leadership to align architecture and platform investments with product, research, and business priorities.

Analyze frontline operations performance across specialists, queues, vendors, and sites. Identify root causes behind SLA, AHT, accuracy, and utilization changes; quantify impacts; monitor emerging issues; and provide actionable recommendations to operations leadership. Define requirements for specialist metrics and dashboards, collaborate with analytics and support teams, explain findings in business reviews, and use AI analytics tools to accelerate investigations.

Leads the full digital experience research lifecycle, including user interviews, testing, surveys, behavioral analysis, experimentation, and conversion optimization. Defines research and web measurement strategies, analyzes qualitative and quantitative data, builds dashboards and executive presentations, and translates findings into compelling data stories. Partners with marketing, technology, design, product, and development teams to improve global web experiences, while maintaining scalable research documentation and insight repositories.

Develops advanced operations research models, analytics, decision-support tools, and data solutions for transportation and network optimization. Responsibilities include collecting and analyzing data, evaluating systems and networks, identifying performance improvements, building predictive and prescriptive models, presenting recommendations to senior management, leading projects, and mentoring other operations research professionals.

Lead design, build, and operate scalable Databricks/Delta Lake data pipelines and Kimball dimensional models using dbt. Manage governance with Unity Catalog, optimize performance and cost, operationalize ML with MLflow, and coordinate/quality-check offshore vendor engineering. Mentor engineers, uphold standards, and deliver trusted data products that power analytics, reporting, and MLOps workflows.