Top Remote Analysis Reporting Jobs in Greensboro, NC

Designs and supports enterprise data integrations, ETL/ELT pipelines, APIs, data models, and transformations across Microsoft platforms. Maintains data quality, governance, security, and reliability while developing CI/CD pipelines, deployment automation, and release processes. Troubleshoots integration and deployment issues, manages environments, supports reporting and analytics, and collaborates with technical and business stakeholders to deliver scalable data solutions.

Designs and delivers analytics solutions on Snowflake using dbt, SQL, and modern ELT practices. Responsibilities include data modeling, pipeline development, migrations, performance optimization, data quality, security, orchestration, CI/CD, and release management. Leads discovery and requirements gathering, translates business needs into analytics architectures, provides technical guidance, and communicates recommendations to client stakeholders in agile consulting environments.

Build risk data models, analyze fraud and risk trends, create Tableau dashboards and automated reports, and deliver actionable insights to Risk Operations leaders. The role manages analytics requirements and roadmaps while using SQL, dbt, Dataform, and AI tools to support fraud strategy, compliance monitoring, loss forecasting, and executive reporting.

Leads Gartner research and thought leadership on data management, governance, and AI. Develops actionable insights, analyzes market trends, advises executive clients, delivers presentations, supports sales and conferences, reviews content, improves research processes, and mentors analysts. Requires deep expertise in data and analytics, AI implementation, data security, data value creation, executive communication, research, and strategic analysis. Remote U.S. role with travel up to 25%.

Design and own an event-driven data architecture that moves healthcare claims data through AWS and Snowflake into fraud, waste, and abuse alerts. Establish architecture standards, approve material changes, build complex pipeline components, and ensure scalability, reliability, and compliance with PII/PHI constraints. Collaborate with data science, compliance, technical, and investigative teams while supporting government review timelines. This is a hands-on principal role requiring strong Python, SQL, AWS, Snowflake, and production streaming pipeline experience.

Build and maintain IICS ETL/ELT pipelines, develop Amazon Redshift data models, and use SQL and Python for data transformation and automation. Create Power BI reporting models, implement data quality checks, document pipelines, and collaborate with client stakeholders and engineering teams. The role requires autonomous work, strong communication, and the ability to translate technical solutions into business context, with bonus value for Veeva or life sciences experience.

Leads legacy data migration into SaaS platforms by assessing sources, designing conversion strategies, executing ETL workflows, mapping and transforming data, validating integrity, and managing PII. Engages clients to gather requirements, document business processes, support governance and data quality, coordinate implementation teams, and develop reusable methodologies and training materials.

Develop and optimize enterprise Oracle SQL and PL/SQL solutions, including data models, database designs, APIs, ETL processes, batch jobs, and performance tuning. Collaborate with cross-functional teams to translate requirements into scalable implementations, support testing and CI/CD, troubleshoot production issues, and document solutions. Provide technical leadership, mentor engineers, participate in architecture and code reviews, and drive engineering best practices across data modernization initiatives.

Own data quality across systems by designing validation rules, reconciliation processes, profiling workflows, and quality controls. Investigate discrepancies to identify root causes, apply statistical methods to detect anomalies, evaluate machine learning model outputs, and communicate findings to technical and non-technical stakeholders. Partner with engineering, BI, and business teams to establish data quality standards, metrics, controls, and reporting practices.

Maintains global services pricing data by executing price changes and service mappings, auditing data integrity, resolving discrepancies, and translating business requirements into actionable insights. Partners with product, finance, and other stakeholders, supports competitive benchmarking, and develops repeatable processes to improve pricing operations and scalability.