Top Data & Analytics Jobs in Tulsa, OK

Design and lead scalable data engineering solutions across Databricks and Microsoft Azure. Define enterprise data modeling standards, architect pipelines and integrations, establish engineering best practices, troubleshoot complex platform issues, and guide modernization and cloud migration initiatives. Provide technical leadership and mentorship while ensuring data platforms meet security, quality, governance, reliability, performance, and maintainability standards.

Builds and maintains scalable data pipelines, ETL infrastructure, data warehouses, and analytics tools. The role assembles complex datasets, automates processes, optimizes data delivery architecture, and supports cross-functional data initiatives. Collaborates with executive, product, data, and design stakeholders to resolve technical issues and improve analytics systems. Requires proficiency in SAS, Python, Java, MATLAB, SQL, NoSQL, Hadoop, MapReduce, Hive, Presto, UNIX, and Linux, with JavaScript, R, and basic machine learning preferred.

Owns the company’s BI platform and data strategy across clinical, operations, finance, and HR functions. Responsibilities include setting the analytics product roadmap, governing data definitions and PHI, managing platform architecture, building dbt models and dashboards, delivering healthcare quality and value-based-care analytics, deploying conversational AI, coordinating vendors and multi-team programs, and developing an analytics team. The role requires hands-on ownership of clinical data, EHR integrations, semantic modeling, governance, and executive reporting.

Build and operate large-scale data pipelines, web-scraping systems, and data-collection tools for AI datasets. Maintain analytical databases, optimize queries, troubleshoot pipeline and data-quality issues, manage containerized workloads across Kubernetes and Linux infrastructure, and support CI/CD workflows. The role also involves documenting technical processes, researching improvements, and developing scalable APIs in a fully remote environment.

Conducts public health data validation, management, quality assurance, geospatial and molecular HIV analysis using SAS and R. Responsibilities include developing codebooks and data management plans, identifying discrepancies, performing duplicate and comparison procedures, generating reports, interpreting results, disseminating data, and collaborating with analysts, federal partners, jurisdictions, and community-based organizations.

Build, test, maintain, and enhance Workday financial reports, dashboards, and reporting solutions. Gather requirements, validate and reconcile data, document report logic, troubleshoot performance issues, support Workday implementations and releases, and train end users. Partner with Finance, HR, Supply Chain, and other stakeholders to ensure accurate, compliant, and actionable reporting across a nonprofit healthcare system.

Leads the design and delivery of scalable data pipelines, dbt models, orchestration workflows, and analytical data models. Establishes data architecture, engineering standards, quality frameworks, governance, observability, and self-service analytics practices. Partners with stakeholders, leads technical reviews, mentors engineers, supports hiring, oversees analyses, and participates in incident response and continuous improvement.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake. Architect data foundations to power AI and LLM-enabled workflows, operationalize core SaaS metrics, and build reusable data assets for analytics and activation. Partner cross-functionally to embed analytics into workflows and ensure scalable, secure architecture.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake; architect reusable data assets, governance, and SaaS metrics; build AI-enabled data foundations and LLM workflows; integrate analytics into operational tools and partner cross-functionally to productionize AI-driven use cases.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.