Top Remote Analysis Reporting Jobs in Tulsa, OK

The Senior Data Engineer will focus on Data Modeling, utilizing SQL, Snowflake, and Apache Airflow to develop efficient data models and deliver data products.

The Growth Analyst supports capture efforts by producing decision-support artifacts from source documents, using Excel and AI tools for effective organization and analysis of information.

Lead the transformation of insurance operations into scalable solutions on the Majesco platform, ensuring alignment with product architecture. Guide clients through the implementation of insurance strategies across policy administration, billing, claims, and digital experiences.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.

Trace3 seeks enthusiastic individuals for its Data Intelligence Team. The role focuses on innovative technology solutions and consulting services, fostering a collaborative and dynamic work environment.

The Data and Analytics Consultant will design, develop, and implement data reporting, visualizations, and analytics solutions for clients while assisting them in data understanding and value extraction.

Lead a team of Data Scientists and Analysts, developing AI and data-driven solutions, driving analytics insights, and fostering collaboration across teams.

Lead oversight of data management for assigned studies, manage external vendors, review and approve DM documentation, perform secondary UAT of EDC, implement RBQM oversight, and provide cross-functional input on protocols and study deliverables to ensure data quality and regulatory compliance.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.