Top Senior Analysis Reporting Jobs in Wilmington, NC

Lead complex customer analytics engagements, translating industrial business needs into scalable analytics architectures and solutions. Advise customers, drive product adoption, identify high-value use cases, mentor Analytics Engineers, resolve technical escalations, and influence product roadmaps. Apply expertise in industrial process data and sectors such as power, pharmaceuticals, and semiconductors. Collaborate with customers, partners, product teams, and account teams to deliver measurable business outcomes.

Leads and develops the Data Engineering team while remaining hands-on with scalable pipelines, ETL/ELT processes, data warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical strategy; improves automation and monitoring; and partners with Finance and business stakeholders to translate data needs into practical solutions.

Designs, develops, and maintains Databricks-based ETL pipelines, data lake architectures, datasets, and data warehouses supporting reporting, analytics, and AI/ML workloads. Troubleshoots and optimizes Databricks and SSIS processes, maintains SSRS reports, implements data quality controls, migrates legacy systems, and collaborates with business and technical teams. The role also promotes AI-assisted development practices and documents technical procedures.

Designs, analyzes, documents, integrates, and migrates complex environmental datasets for AirHub business lines. Responsibilities include analyzing legacy databases, creating logical and physical data models, documenting mappings and business rules, developing migration specifications and API integrations, supporting data governance and testing, and producing technical documentation. The role also requires close collaboration with business stakeholders in an Agile delivery environment.

Designs enterprise-scale federated data architectures integrating Palantir Foundry and Databricks. Establishes data-sharing, governance, lineage, metadata, and ownership standards across cloud platforms. Leads legacy ETL modernization, builds scalable PySpark and Spark SQL pipelines, architects secure connectivity, and enables AI, machine learning, real-time analytics, and self-service data products. Serves as the technical authority, leads architecture reviews, and manages stakeholder relationships.

The Senior Data Analyst gathers business and data requirements, assesses data quality and sources, maintains data dictionaries and lineage, defines KPIs, validates reports, and delivers actionable insights. The role supports data governance, PII protection, integrations, data transformation, platform performance, business continuity, and process improvement. It collaborates with stakeholders and data teams, mentors colleagues, resolves complex issues, and contributes to enterprise data strategy and technology decisions.

Lead financial data engineering initiatives involving commissions, incentive programs, and backend financial systems. Build scalable, accurate, and reliable data pipelines, platform tooling, partner integrations, analytics infrastructure, and data science infrastructure. Shape technical strategy and roadmaps, collaborate with Finance, Product, Data Science, and Engineering, mentor engineers, contribute code, lead incident response, and establish engineering standards.

Develop and deploy business intelligence applications for a U.S. Air Force financial platform across development, testing, integration, and production environments. Design and optimize Informatica ETL pipelines, Oracle databases, SQL and PL/SQL processes, data warehouses, BI semantic layers, and SAP integrations. Support Agile delivery, budgeting integrations, monitoring, interface changes, and security hardening. The role also requires Oracle APEX, WebLogic, HTTP Server, performance tuning, and collaboration on data-related issues.

Develops scalable data models, Databricks pipelines, backend applications, ETL processes, and data ingestion systems. Partners with engineering, product, and business stakeholders on technical roadmaps; monitors and optimizes data systems for performance, reliability, and scalability. Provides technical leadership, mentors junior engineers, conducts code reviews, and builds secure solutions for sensitive healthcare data.

Designs, builds, and maintains scalable data pipelines, data models, and platform infrastructure supporting enterprise reporting, analytics, and AI-driven decisions. Responsibilities include ingesting SaaS application data, developing medallion architecture layers and dbt transformations, implementing data quality monitoring, enforcing governance and access controls, and delivering reusable semantic data assets. The role collaborates with analytics, BI, and business teams, participates in Agile delivery, evaluates modern data-stack tools, and promotes engineering excellence through testing, documentation, and code reviews.