Top Data & Analytics Jobs in Oklahoma City, OK

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Leads complex data and reporting solutions across the product lifecycle. Partners with customers, engineers, architects, vendors, and project teams to gather requirements, build datasets, reports, and dashboards, analyze business problems, manage testing, resolve defects, assess risks, and deliver improvements. Provides subject matter expertise, strategic direction, customer communication, cost-benefit analysis, compliance oversight, and mentorship to data analysts.

Develops data infrastructure, analytics solutions, prototypes, and enterprise data assets supporting data science and predictive modeling. Collaborates with data scientists, engineers, and business partners to define requirements, build and test solutions, support user acceptance, and deliver rapid data engineering work tracks. Uses SQL, Python, and Spark for agile data analysis and parallel processing. Also contributes to proof-of-concept designs, documentation, process improvement, and team mentoring.

Build GCP data pipelines, ETL/ELT processes, integrations, data models, dashboards, and analytics solutions. Support Vertex AI and Gemini-based ML, MLOps, prompt engineering, embeddings, and RAG initiatives. Participate in client workshops, requirements gathering, data governance, quality checks, security practices, testing, monitoring, and technical implementation under senior guidance.

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

Uses SQL, Excel, Dataiku, Python, and related tools to analyze pharmacy network changes, assess client disruption, retain and win business, and produce standard and custom reports. Responsibilities include data cleaning, transformation, ETL, reporting process improvements, complex data interpretation, and managing multiple analytical priorities across business lines and clients.