Top Senior Data & Analytics Jobs in Raleigh, NC

Analyze reinsurance data and business processes, gather requirements, create data mappings and flow diagrams, and support FAIRR Data Hub solutions. The role validates data quality, governance, reconciliation, and technical specifications while partnering with business, technology, architecture, engineering, and governance teams. It also contributes to reporting, AI-enabled analytics, solution testing, stakeholder communication, and mentoring junior analysts.

Leads enterprise healthcare data engineering strategy, cloud data platform modernization, warehouse and lakehouse architecture, ETL/ELT pipelines, streaming, interoperability, governance, data quality, and master data management. Manages data engineering, analytics, and platform teams while supporting AI/ML initiatives. Requires extensive healthcare data experience, leadership of large programs, cloud and data engineering expertise, knowledge of claims and clinical systems, and familiarity with HL7, FHIR, EHR platforms, and healthcare compliance.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

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.

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.

Lead analytics consulting engagements by translating business objectives into analytical roadmaps, defining and governing KPIs, assessing data quality, and conducting hands-on data exploration using SQL and Python. Partner with stakeholders and Power BI developers to design metric structures, semantic models, wireframes, and dashboards that support strategic decision-making.

Designs and develops scalable cloud-based data platforms and architectures for consulting clients. Translates business objectives into technical solutions, supports data warehousing, business intelligence, master and reference data management, and develops Big Data platforms using Azure or AWS. Leads client initiatives, establishes architectural governance, creates system diagrams, collaborates with stakeholders and vendors, and mentors data architects and engineers.

Develop scalable data engineering solutions for Fidelity’s asset management technology platform. Responsibilities include designing data models and ETL pipelines, developing Oracle PL/SQL and SQL solutions, tuning database performance, supporting Snowflake data warehouses, and applying DevOps and Agile practices. The role also provides production support through an after-hours on-call rotation, including troubleshooting and incident response.

Leads destination and tourism research, including brand studies, visitor analysis, economic impact measurement, sentiment surveys, and brand-lift evaluation. Manages research vendors, study timelines, surveys, qualitative research, data quality, reporting, and economic impact methodologies. Translates complex findings into recommendations, presentations, media content, advocacy materials, and stakeholder insights. Partners across marketing, communications, sports, tourism, and community organizations while maintaining recurring research and performance reporting.

Designs, develops, integrates, and supports modern data solutions for healthcare claims, revenue, Medicare, and payer data. The role includes on-premises data warehousing, cloud migrations, SQL and Python/PySpark development, dimensional modeling, troubleshooting, performance optimization, and process improvement. The engineer collaborates with engineering, analytics, data science, and product teams in an agile environment.