Top Senior Analysis Reporting Jobs in Wilmington, NC

Develops and maintains Salesforce and Tableau analytics dashboards, performs complex data analysis and forecasting, and delivers insights for sales, product, finance, and marketing decisions. Translates business needs into technical requirements, manages platform enhancements with developers, validates data quality, models sales goals, identifies optimization opportunities, and presents strategic recommendations. Provides user training and supports analytics across Treasury Solutions.

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Build forecasts, financial models, dashboards, datasets, and automated reporting workflows for Deposits and Treasury Management. Analyze market conditions, deposit pricing, portfolio performance, funding, liquidity, and costs. Use Databricks, SQL, Python, Excel, BI tools, and AI tools to modernize processes and deliver executive- and board-ready insights. Partner with Treasury, Finance, Marketing, Embedded Banking, and Merchant Services while maintaining regulatory awareness.

Design and evolve enterprise data architecture and models (conceptual, logical, physical). Lead LDM/PDM development, run JAD sessions, apply naming standards, use data profiling and modeling tools, review models with SMEs, coordinate multi-stream teams and third parties, and communicate architecture to senior stakeholders.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Lead Workday reporting strategy for higher education: design Advanced, Matrix, Composite, and Dashboard reports; implement row-level security and role-based access; partner with HR/Finance/Payroll/Institutional Research; support regulatory and executive reporting; manage testing, validation, and user training while ensuring governance and data standards.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Build and operate batch and near-real-time data pipelines, semantic models, certified measures, APIs, and serving infrastructure for AI-powered decision systems. Responsibilities include data quality, observability, lineage, governance, CI/CD, infrastructure as code, performance optimization, model scoring pipelines, and AI telemetry. Partner with data scientists and business stakeholders to productionize models and deliver reusable, documented data platform capabilities.