Top Remote Data & Analytics Jobs in Tulsa, OK

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

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.

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 a marketing analytics team to deliver acquisition, engagement, retention, and reactivation measurement. Own SQL-based analyses, experiments, audience strategies, dashboards, and incrementality methods. Translate business questions into analytical plans, partner cross-functionally, mentor analysts, and connect marketing activity to downstream outcomes like retention, revenue, and lifetime value.

Lead a team delivering product and business analytics for Fetch's commerce and shoppable experiences. Own prioritization, experimentation, measurement, KPI dashboards, and stakeholder-facing insights to inform product, marketing, and commercial decisions. Manage and develop analysts while partnering cross-functionally to ensure data quality, repeatable analyses, and actionable recommendations.

Lead technical advisor for enterprise data visualization and BI initiatives. Design semantic models and reporting architectures, implement Power BI and Microsoft Fabric solutions, optimize performance and security, run discovery workshops and executive advisory sessions, enable governed self-service and accessibility, and drive analytics adoption and AI readiness across clients.

Lead technical advisor for enterprise data governance engagements. Design governance strategy, metadata management, business glossaries, taxonomy, data lineage, stewardship models, and Microsoft Purview implementations. Run workshops, maturity assessments, and executive advisory sessions. Create governance monitoring, operational reporting, and AI-readiness assessments for platforms like Microsoft Fabric, Power BI, and Azure.

Senior Data Architect contractor to accelerate and modernize the data platform: assess landscape, design end-to-end data solutions, define integration and metadata patterns, enable data mesh and cloud migration (AWS), and produce reusable architecture artifacts for handoff to engineering teams.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Analyze business data, build and maintain business models, provide actionable insights and reports, collaborate with cross-functional teams, monitor performance, and recommend efficiency improvements to support strategic decision-making.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

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.

Design, build, and maintain scalable data pipelines and ETL/ELT frameworks using Python and PySpark. Develop reusable components, microservices, and cloud-based data solutions on AWS and Snowflake. Ensure code quality via reviews, CI/CD, logging, and best practices while collaborating with stakeholders to solve data problems.