Top Senior Data & Analytics Jobs in Oklahoma City, OK

Own client-facing analytics and attribution: establish baselines, implement tracking and lead-to-sale matching, run holdout and lift experiments, quantify cost avoidance, build cross-client benchmarks, and translate findings into clear ROI narratives that inform pricing, product, and renewal conversations.

Transform commercial, market, consumer, and portfolio data into actionable insights. Build and maintain dashboards and KPI reporting, analyze performance and competitive trends, support pricing, assortment, and launch decisions, and deliver executive-ready recommendations while partnering with cross-functional teams to ensure data quality and commercial alignment.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Partner with stakeholders to translate business needs into BI requirements, design and maintain BI solutions and semantic layers, analyze large payment datasets, enforce data governance and quality, deliver insights and reports, lead stakeholder meetings and training, mentor team members, and drive process improvements for data loading and analytics.

Design and own a federated, multi-institution medallion lakehouse on Azure Databricks and Microsoft Fabric. Define federated multi-tenant architecture, Unity Catalog security, data ingestion from ERP/SIS/LMS/CRM/Workday, and platform standards. Provide hands-on architecture guidance, review designs, document decisions, and partner with governance, delivery, and engineering teams to enable production analytics at multiple institutions.

Design and build Snowflake transformation layer and migrate legacy SQL to versioned dbt models. Define conformed dimensions/facts using Kimball principles, set modeling and CI/CD standards, implement data quality/lineage, support BI migration and AI/ML readiness, and mentor future hires. Hands-on work in dbt, SQL, and Python with stakeholder collaboration and governance for financial and operational data.

Develop and maintain automated ETL solutions using SSIS, Oracle SQL, and PL/SQL to move data between Oracle and SQL Server systems. Design database, data warehouse, and ETL interfaces; analyze requirements; establish development, documentation, and testing standards; manage change deployments; and monitor project schedules. Collaborate with stakeholders, assess database changes and downstream impacts, document solutions, communicate issues, and mentor junior staff.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

Lead current-year and long-term AP volume forecasting using statistical and AI/ML methods; diagnose supply-demand drivers; close analytic data gaps; translate analyses into strategic recommendations; mentor staff and communicate forecasts and risks to senior stakeholders across College Board.

Validate and triage clinical data across HL7, FHIR, and Databricks pipelines using SQL. Trace transformations end-to-end, identify and remediate data quality issues, partner with engineering/product/clinical teams, document findings, and support client go-lives to ensure clinically accurate, production-ready data.