Top Senior Analysis Reporting Jobs in Oklahoma City, OK

Lead and mentor a distributed data engineering team while architecting and building a next-generation, largely open-source data platform. Own hands-on POCs, pipeline design, schema and query optimization, ETL reliability, observability, testing, and CI/CD. Evaluate and recommend technologies, drive migration from vendor lock-in, and translate advertising and market research needs into robust technical solutions.

As a Senior Analyst, you will develop data-driven solutions in collaboration with operations teams and deliver insights through reports and dashboards to improve patient outcomes.

Own Splash's growth analytics and attribution stack (AppsFlyer, Segment, Snowflake, dbt). Build attribution and LTV/CAC/payback models, maintain pipelines and reporting, drive funnel and contest analysis, reconcile ad spend to revenue, mentor junior analysts, and partner with marketing, product, and finance to inform budget and growth decisions.

Design, build, and maintain production ETL/ELT pipelines, analytics-ready data models, and cloud data infrastructure. Improve pipeline performance, data quality, governance, and migrate legacy systems to modern platforms. Collaborate with stakeholders to translate business requirements into reliable data products for project, financial, and operational analytics.

The Global Head of Pricing will lead pricing functions, optimize margins, develop pricing models, and ensure accurate billing while partnering with multiple teams.

Use statistical modeling and data analysis to generate actionable insights that improve loan origination and production. Collaborate cross-functionally to design, test, and implement solutions, build dashboards and visualizations, maintain data integrity, and communicate findings to stakeholders to inform business strategy.

The IT Senior Analyst will gather requirements, lead testing, manage integration projects, and mentor team members in a high-paced environment.

Build and own the quality analytics data layer: design and maintain dbt models, data marts, and Python-driven analyses. Define and standardize quality metrics, run experiments and A/B tests, support decision-making with dashboards and reports, automate recurring reporting, and partner with Quality and Engineering to ensure reliable, documented analytics.