Top Senior Data & Analytics Jobs in Raleigh, NC

Analyze complex datasets, develop data models, dashboards, and visualizations, and conduct predictive and statistical analysis for client decision-making. Collaborate with clients to deliver tailored analytics solutions, maintain data integrity, communicate insights through reports and presentations, and support data-driven operational strategies using SAS, Power BI, Tableau, and SQL tools.

Architects and optimizes enterprise ETL processes and large-scale data pipelines using Databricks, Spark, SQL, and Python. Develops data models, incremental loads, Power BI dashboards, and semantic models. Partners with business and product leaders to deliver automated data solutions, leads global ETL coordination, evaluates emerging AI and ETL technologies, and designs responsible AI-powered analytics solutions.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

Design, build, and maintain BI-ready datasets, dashboards, and monitoring tools for high-throughput lab operations. Implement process monitoring (SPC), ensure data quality and audit readiness, perform root-cause analysis, and partner with Data Science to deploy predictive models that improve throughput, quality, and compliance.

Build and maintain AI billing, metering, consumption, and allocation data models. Reconcile usage and billing data across vendors, ensure data quality, and develop dashboards showing costs, utilization, trends, variances, and budget performance. Investigate anomalies and optimization opportunities while partnering with technology, finance, and business stakeholders on forecasting, governance, chargeback, cost transparency, and AI investment decisions.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

Develops, maintains, and analyzes manufacturing reports, ensuring timely delivery, accuracy, and data integrity. Monitors existing reports for data changes and discrepancies, translates complex information into user-friendly insights, and communicates key takeaways to internal customers and management. The role requires expertise with ERP, TMS, inventory systems, Excel, and Power BI, along with manufacturing, supply chain, or analytical experience. Work occurs in warehouse and office environments with frequent lifting and standing.

Designs and leads enterprise-scale data platforms, pipelines, lakehouse, warehouse, and streaming solutions. Establishes data modeling, governance, security, and architecture standards while optimizing performance, reliability, scalability, and cost. Collaborates with data engineering, analytics, machine learning, and business teams, mentors engineers, and drives best practices across data platforms.

Lead modernization of an on-premises SQL Server investment management data warehouse into a governed, cloud-native platform on Google Cloud. Oversee BigQuery architecture, data modeling, pipelines, reporting, Looker analytics, Vertex AI enablement, security, governance, and operational resilience. Manage technical teams, develop engineering talent, coordinate complex stakeholder programs, and translate business priorities into technology plans.

The Analysis Oversight Statistical Programming Lead is accountable for statistical programming deliverables, vendor performance monitoring, and team leadership within clinical studies.