Top Senior Analysis Reporting Jobs in Wilmington, NC

Leads the design and implementation of AI-powered data pipelines, enterprise feature stores, analytics-ready repositories, and self-service data access layers. Builds automated feature engineering, data quality, observability, and governance capabilities for large-scale data science workloads. Partners with Enterprise IT, establishes data availability and quality SLAs, integrates structured and unstructured data sources, and leads teams delivering scalable analytics infrastructure.

Reviews AI-generated documents, spreadsheets, and slide decks for accuracy, rigor, presentation quality, and domain-specific compliance. Evaluates outputs using quality rubrics, identifies factual and aesthetic errors, and provides structured written feedback. The role requires deep expertise in data quality and CRM operations, strong English fluency, and proficiency with Microsoft Office and Google Workspace. It is a fully remote, flexible independent-contractor engagement.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Analyze platform, product, customer, advertising, and operational data to generate actionable insights. Build dashboards, reporting frameworks, automated workflows, and scalable analytics pipelines. Evaluate experiments and analytical methodologies, improve forecasting and data accuracy, and partner with product, engineering, marketing, revenue, and leadership teams to influence strategy, customer experience, and platform growth.

Lead data engineering initiatives that build scalable warehouses, pipelines, ETL/ELT processes, dashboards, and automated reporting workflows. Translate finance and operational needs into reliable data solutions, implement governance and quality practices, and support integrations, migrations, acquisitions, and system enhancements across portfolio companies. Partner directly with finance, accounting, analytics, and operational stakeholders to improve decision-making.

Senior Business Intelligence Analyst who develops and governs Power BI dashboards, analyzes clinic performance metrics, ensures reporting accuracy, and translates operational needs into technical requirements. The role manages BI projects end to end, prioritizes analytics tickets, presents insights to executive stakeholders, establishes reporting standards, contributes to data-model requirements, and mentors junior analysts across clinical and corporate operations.

Leads enterprise business intelligence and analytics solutions using Power BI and Microsoft Fabric. Designs semantic models, certified datasets, dashboards, DAX calculations, data transformations, security controls, and governed self-service analytics. Assesses and modernizes reporting portfolios, develops predictive and forecasting capabilities, gathers requirements, validates data quality, supports documentation and adoption, and mentors analysts. Collaborates with business, engineering, governance, and security stakeholders to establish scalable enterprise analytics standards.

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.

Manages and evolves enterprise data lakes and warehouses, designing scalable AWS-based batch, CDC, and near-real-time ETL/ELT pipelines. Builds data quality, governance, lineage, security, monitoring, and recovery controls; optimizes Spark, Glue, Athena, Redshift, and S3 workloads. Develops reusable Python, SQL, and PySpark frameworks, supports schema evolution and analytical data modeling, and collaborates with business and technical stakeholders to deliver reliable data solutions.