Top Data & Analytics Jobs in Tulsa, OK

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.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

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.

Creates business insights, analytics, datasets, and reports to support divisional strategy. Consults with business users, leads cross-functional projects, analyzes internal and external data, identifies trends, validates reporting accuracy, and translates technical findings into actionable recommendations. Builds tools with data teams, develops customer relationships, and supports complex business decisions through research and reporting.

Supports reporting, data analysis, dashboard development, data collection, quality assurance, and data warehousing initiatives. Cleans and analyzes data, generates actionable insights, communicates findings to nontechnical stakeholders, responds to data requests, and partners with KIPP program teams. The role also contributes to network events, team operations, and equity-focused culture development.

Design, build, and maintain scalable AWS-based data pipelines and storage (S3, Redshift, RDS, DynamoDB). Implement IaC (CloudFormation/CDK), ETL optimization, monitoring, security (IAM, OWASP/CIS best practices), and CI/CD/code pipeline controls. Collaborate with product teams, document solutions, and provide training to support analytics and reliable data infrastructure.

Lead and mentor data engineering teams to design, build, and govern enterprise data warehouses, lakes, and lakehouses. Architect scalable ETL/ELT and streaming pipelines, drive cloud migrations, enable BI/AI initiatives, and partner with Finance, Operations, and Supply Chain to deliver analytics and operational reporting.

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.