Top Data & Analytics Jobs in Tulsa, OK

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Own healthcare analytics data methodology, including episode grouping, provider attribution, cost standardization, quality measures, reference data, pipelines, QA, and production delivery. Translate feature requests into specifications and validated analytics. Reconcile results, establish recurring data-quality coverage, investigate failures, and collaborate with engineering, data science, product, clinical informatics, and customer teams. Advanced SQL and healthcare claims expertise are central to ensuring accurate, defensible customer metrics.

Own analytics for Customer Success and Operations by translating ambiguous business questions into metrics, reports, dashboards, and PRDs. Partner with senior leaders, CSMs, Analytics Engineers, and Operations teams to improve retention, permit turnaround, and organizational scalability. Build self-service dashboards, develop dbt models, document analytics assets, prioritize high-impact requests, and use LLM tools to accelerate SQL, reporting, and data-model development.

Build and maintain Snowflake and dbt data platforms, including ELT pipelines, tested models, orchestration, monitoring, documentation, access controls, and governance. Optimize performance and costs while ensuring reliable, discoverable data for internal dashboards, client products, and AI/ML use cases. Translate ambiguous stakeholder needs into durable solutions and apply strong software engineering practices, including Git, CI/CD, code review, Python, testing, and alerting.

Establish and operationalize Finance data governance across Finance and Technology. Define governance models, business glossaries, data inventories, lineage, quality controls, master-data standards, hierarchies, and reconciliation processes. Support SAP, Snowflake, reporting, planning, and analytics data products; facilitate stakeholder workshops; document requirements; manage governance backlogs; and coach data owners and stewards in an ambiguous enterprise environment.

Analyze large datasets using SQL and Python, build dashboards and recurring reports, identify trends and data-quality issues, and translate ambiguous business questions into actionable insights. The role partners with product, customer success, and engineering teams, documents metrics and methodologies, and presents findings to technical and non-technical stakeholders. Healthcare data, supply chain analytics, modern analytics engineering, and BI visualization experience are advantageous.

Build and maintain a regulatory reporting data platform using SQL and dbt, including models, automated validations, data pipelines, and testing. Investigate data issues end to end, validate submissions, support audits and legal data requests, monitor upstream changes, collaborate with product, engineering, compliance, and leadership, and participate in on-call coverage. WOOF WOOF

Leads healthcare data architecture, modeling, normalization, transformation, and integration across FHIR, OMOP, STDM, HL7, and related standards. Oversees data pipelines, terminology mapping, deduplication, quality initiatives, interoperability strategies, and technical documentation. Collaborates across technical and non-technical teams to resolve complex data issues and explore AI and machine learning applications. Requires deep expertise in clinical informatics, healthcare data standards, SQL, Python, R, dbt, ETL, cloud platforms, and version control.

Design, build, and operate production data pipelines using Python, Spark SQL, and Airflow. Canonicalize healthcare and customer data into trusted internal models, optimize distributed processing, enforce schemas, and implement quality checks and observability. Support customer onboarding, streaming pipelines, troubleshooting, on-call operations, and platform best practices while collaborating with product, analytics, engineering, data science, and customer teams.

Administer and optimize production and non-production databases for a large-scale VA data migration. Responsibilities include installation, patching, performance tuning, backup and recovery, security, AWS database provisioning, data conversion, validation, troubleshooting, high availability, disaster recovery, and technical documentation. The role collaborates with developers and analysts across on-premises and AWS environments while ensuring database availability, integrity, and security.