Top Remote Data & Analytics Jobs in Oklahoma City, OK

Build and maintain large-scale data structures and ETL pipelines using Python and SQL. Design data marts and models, integrate data sources, ensure data quality, and collaborate with cross-functional teams to operationalize analytics on cloud platforms.

Lead end-to-end strategic projects to optimize health plan programs, perform data-driven analyses, build impact models, present executive recommendations, advise cross-functional stakeholders, mentor junior analysts, and monitor initiative outcomes to improve efficiency and care quality.

Lead SAP BusinessObjects reporting delivery: gather requirements, design universes and Webi/Crystal/Xcelsius reports, implement data and system security, support clustered BO environments, perform testing and upgrades, mentor juniors, and provide production support and user training for BI/data warehouse solutions.

The Data Integration Engineer will manage data integrations and ETL processes for healthcare data, ensuring accuracy and accessibility for business users.

Partner with business, product, and technical teams to define KPIs, translate business needs into data requirements, build reporting and dashboards for embedded payments (card, ACH, RTP), and drive data governance and continuous improvement.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Analyze business processes and SAP data to identify issues and recommend IS solutions. Perform SAP data mining, BW reporting, master data maintenance, collect/translate requirements, and support continual service improvement and related IS implementations.

The Central Risk Manager is responsible for developing and implementing strategies for Risk-Based Quality Management and Monitoring across clinical trials, collaborating with stakeholders, and leveraging data analytics for risk identification and mitigation.

The Senior Technical Analyst collaborates with stakeholders and engineers to document requirements, ensure quality, and support SDLC activities, while being a trusted advisor on solution design and process impacts.

Drive process improvement and automation by identifying inefficiencies, developing automations and data pipelines, analyzing KPIs, and designing LLM/ML-enabled solutions in collaboration with AI. Support analytics, SQL/Databricks work, and deliver data-driven insights to improve operational efficiency.