Top Data & Analytics Jobs in Tulsa, OK

Design and lead enterprise data warehouse solutions using IBM DataStage, Oracle, Teradata and Cognos. Translate business requirements to technical designs, define data strategy and roadmap, ensure data quality and modeling, establish standards for BI, analytics and Big Data, and coordinate with BI/reporting teams on integrations and deployments.

Implement, build and maintain SAP BW data structures (3.5/7.0/7.3); design/create/modify SAP and non-SAP extractors; schedule Control-M batch jobs; troubleshoot production data issues; liaise with data analysts and customers while meeting project deadlines.

The AWS Data Engineer designs and maintains data solutions on AWS, implementing scalable pipelines, integrating systems, ensuring security, and optimizing workflows.

Design, deploy, and maintain scalable data infrastructure and orchestration for analytics and ML; write optimized SQL over large warehouses; partner with engineering and product to structure source systems; maintain CDC pipelines; scale reporting and expose analytical datasets enterprise-wide while ensuring data management, security, and compliance.

Support building and maintaining ETL/ELT data pipelines and cloud data workflows. Work with senior engineers and cross-functional teams to implement, test, deploy, and document data processes. Continuously learn cloud technologies, SQL, and Python/PySpark, follow coding best practices, and contribute to process improvements in an Agile environment.

Work with clients and technology teams to gather and translate business requirements into technical user stories and solutions, propose process improvements, and communicate effectively with stakeholders. Assist in analytical solution delivery and may write/execute SQL queries.

Review and process laboratory orders, input and verify test data, perform regular data audits, identify and resolve discrepancies, and provide process feedback in a remote environment.

Lead creation and publication of data-driven economic research using Life360 first‑party and external data. Develop seasonal adjustment frameworks, craft public narratives, serve as company spokesperson, partner with Data & Analytics, Product, and Comms, and build data‑storytelling methodology within compute and time-series constraints.

Manage performance, reliability, and accountability for high-volume messaging programs. Build dashboards and alerting, run ad hoc analyses, coordinate incident response and vendor testing, conduct post-incident reviews, and maintain documentation and compliance tracking to inform program decisions and improvements.

The professor will develop and teach courses in computer and data science, advance a research agenda, and engage in departmental collaboration and meetings.