Top Data & Analytics Jobs in Tulsa, OK

The Staff Data Analyst will build Boulevard's product data foundation, create data-driven recommendations, develop dashboards, conduct deep analyses, and foster a data-driven culture within the organization.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Manage end-to-end analytics projects, lead cross-functional teams, ensure client satisfaction, and utilize AI tools to enhance data insights.

The Solution Engineer - Data Engineering Specialist will provide technical leadership in the financial services sector, collaborating with sales teams to demonstrate Snowflake's data platform capabilities while engaging with technical and executive stakeholders.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Develop and run SAS programs to validate and clean surveillance and research data, create codebooks and data plans, perform geospatial and molecular HIV analyses in R, collaborate on novel code and reporting, and support dissemination to federal and external partners while ensuring data quality and documentation.

Lead growth analytics for acquisition and activation funnels: measure channel performance, build data models and KPI reporting, run experiment analysis, and translate insights into business recommendations. Partner with Growth product team and leadership to visualize results and drive strategy.

Analyze marketing channel performance (Paid Media, CRM, Email, engagement), prepare recurring reports, consolidate data into actionable summaries, perform QA on reports/datasets, support client recommendations and optimizations, collaborate with cross-functional teams, and use AI tools responsibly to improve efficiency.

Analyze customer and caregiver data to identify workflow improvements, build dashboards and visualizations, support Customer Success with QBRs and presentations, translate findings into actionable recommendations, and create scalable data processes while advising Product and Engineering.