Top Data & Analytics Jobs in Tulsa, OK

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

Serve as the primary data partner for Fundraising & Marketing: design and build source-of-truth data models in the lakehouse, create forecasts and donor cohort analyses, automate reporting and data products, support experiment design and ROI measurement, partner with engineering and Salesforce to improve data quality, and translate insights for leadership to drive fundraising strategy.

As a Senior Data Analyst, you'll provide actionable insights by analyzing product and engineering data, partnering with leadership on metrics frameworks and decision support for product delivery.

Lead data engineering initiatives to design and deploy data infrastructure. Optimize data warehouses and automate reporting, ensuring data accuracy and governance.

Analyze product performance metrics and user behavior to drive insights for product improvements. Collaborate with teams to develop reporting practices, A/B tests, and dashboards to inform strategy.

The Head of Lottery Data Engineering & Data Warehousing leads the strategy and delivery of the lottery data platform, ensuring quality, compliance, and efficiency in data processing and storage across jurisdictions and products.

The Senior Data Analyst will collaborate across teams to provide insights, build analytics databases, create dashboards, and automate reporting solutions. They will analyze data trends and partner with IT and product teams to enhance data models.

The Data Engineer will develop and maintain data pipelines, build data models, ensure data quality, and support cross-functional teams while improving internal data platform infrastructure and documentation.