Top Remote Analysis Reporting Jobs in Raleigh, NC

Supports client analytics and business-systems engagements by preparing, validating, mapping, and analyzing data; configuring and testing ERP systems; creating Tableau visualizations and reports; documenting processes; supporting data integration; and communicating with stakeholders. The role works under Lead Analyst guidance while developing ERP, consulting, and account-facing expertise.

Leads scalable data model and pipeline design, dbt development, testing, CI/CD, and analytics engineering implementations. Partners with analysts, engineers, and stakeholders to translate business needs into reliable models and semantic layers. Advises on data architecture, governance, quality, performance, and long-term scalability while mentoring peers and contributing to shared tooling, standards, and frameworks.

Develops and supports data architecture and medical imaging informatics solutions on the XNAT platform. Responsibilities include data integration, modeling, storage and delivery optimization, data-sharing, coding, testing, release management, defect reduction, technical documentation, and partner support. The role collaborates with research and clinical teams, oversees stable XNAT releases, and advances platform capabilities. Required qualifications include a bachelor’s degree or equivalent experience, five years of data-related experience, and PostgreSQL skills.

Leads complex analytics initiatives and partners with business leaders to define problems, analyze pharmacy, sales, and operational data, and develop actionable recommendations. Manages engagements across the full analytics lifecycle, from discovery through solution delivery and implementation support. Designs metrics, dashboards, frameworks, and decision-support tools while communicating insights to executive, operational, and technical audiences. The role emphasizes consultative analytics and business problem solving rather than software development or data infrastructure engineering.

Develops and maintains end-to-end BI dashboards, reporting, and analytics solutions. Partners with leaders to define KPIs, optimize SQL and BI models, ensure data accuracy and governance, and support regulatory reporting. Uses healthcare data to deliver actionable insights, improve processes, and guide strategic decisions. Advises senior leadership through clear, data-driven communication while working with complex datasets and cross-functional teams.

Designs, develops, and maintains ETL/ELT pipelines connecting SAP and other financial source systems to an enterprise budgeting and forecasting platform. Responsibilities include source-system analysis, data mapping and transformation, CDS view and SQL development, data quality validation, reconciliation, troubleshooting, performance tuning, documentation, and collaboration with technical and client stakeholders. The role requires strong SAP data integration expertise, financial data knowledge, and the ability to obtain a Public Trust clearance.

Design, develop, and maintain ETL/ELT pipelines connecting financial source systems such as SAP ERP, General Ledger, and HR systems to a budgeting and forecasting platform. Responsibilities include source-system analysis, data mapping and transformation, CDS and SQL development, data quality validation, troubleshooting, performance tuning, documentation, and collaboration with technical and client stakeholders. The role requires expertise in SAP platforms, financial data structures, reporting, and data integration.

Designs, develops, and maintains ETL/ELT pipelines connecting financial source systems such as SAP and HR systems to budgeting and forecasting platforms. Responsibilities include source-system analysis, data mapping and transformation, CDS views and SQL development, data quality assurance, reconciliation, performance tuning, troubleshooting, documentation, and collaboration with technical and client stakeholders.

The Business Analyst gathers and prioritizes business requirements, supports technology platform design and implementation, maintains process and stakeholder knowledge, conducts software testing and quality assurance, assists with project planning, and trains end users. The role collaborates with vendors, IT, operations, underwriting, and distribution teams to align technology solutions with business needs, KPIs, and the organization’s technology roadmap.

Staff Data Engineer responsible for defining data architecture strategy, building fault-tolerant batch and real-time streaming infrastructure, and managing scalable lakehouse and database systems. The role processes telemetry from millions of connected devices, drives performance tuning and data quality, supports on-call operations, evaluates modern technologies, and mentors engineers. It requires strong expertise in Python, SQL, cloud data platforms, streaming systems, infrastructure as code, and enterprise-scale architecture.

Analyzes institutional data, surveys, student success metrics, enrollment trends, academic information, and KPIs. Prepares internal and external reports, data visualizations, statistical analyses, and presentations supporting university planning, accreditation, strategic initiatives, grants, and program reviews. The role also provides survey design and data-analysis consulting to university departments and ensures data integrity.

Designs, builds, and maintains batch and near-real-time data pipelines and curated datasets for insurance and annuity reporting, analytics, and business operations. Translates business requirements into integration solutions using SQL and ETL tools, implements data quality and reconciliation controls, optimizes workflows, documents lineage, and supports testing, deployment, monitoring, and issue resolution. Works independently on moderately complex pipelines while escalating architectural decisions to senior engineers or data architects.

Own end-to-end data workflows, including ingestion, storage, orchestration, transformation, validation, and delivery. Build ETL/ELT pipelines, manage cloud data platforms and transfers, optimize data models and queries, maintain data quality monitoring, troubleshoot production issues, and document data flows. Collaborate with technical and nontechnical teams to investigate discrepancies, support enterprise datasets, and apply secure data-handling practices.