Top Analysis Reporting Jobs in Tulsa, OK

Leads enterprise data platform architecture, engineering standards, technical decisions, and development of scalable data products. Designs batch and streaming systems, governance, observability, security, and reliability practices. Partners cross-functionally, mentors engineers, drives modernization and migrations, and establishes reusable patterns for data modeling, orchestration, quality, and platform operations.

Lead the architecture and implementation of scalable, secure cloud data platforms for Nokia’s photonic integrated circuit operations. Build high-performance batch and streaming pipelines, enterprise data models, quality and observability frameworks, DataOps automation, governance, and AI-ready data foundations. Enable trusted self-service analytics and AI-assisted exploration while leading and mentoring product engineering teams and driving technical excellence.

Conduct pretesting, item analysis, IRT, score maintenance, data extraction, statistical reporting, and quality control for SAT assessments. Develop and maintain Python and R-based data management and statistical workflows, improve operational processes, document procedures, and evaluate AI-enabled tools. Collaborate with psychometricians and cross-functional teams to deliver accurate assessment data and reports under strict deadlines.

Collects, processes, and analyzes data from multiple sources using R, Python, and SQL. Develops reports, visualizations, analytical methods, and data-driven insights while applying statistical and introductory machine learning techniques. Collaborates with internal and external stakeholders, documents project progress in JIRA, debugs code, clarifies requirements, and communicates findings through reports and presentations.

Leads and develops a data engineering team implementing Navigate360 integrations for partner campuses. Oversees integration design, data mapping, validation, reconciliation, quality controls, delivery planning, and scalable implementation processes. Partners with Product, Launch, and Partner Success teams to resolve technical and partner challenges, improve adoption, manage project health, and ensure reliable outcomes. Provides technical mentorship, code and design review, stakeholder communication, and continuous process improvement.

Supports public health data extraction, management, cleaning, validation, harmonization, statistical and qualitative analysis, and evaluation. Develops analytic datasets and documentation, analyzes implementation and outcome measures, integrates mixed-methods data, and prepares technical memoranda, reports, tables, figures, and presentations. The role also uses Microsoft Office and CDC administrative systems while supporting government program monitoring and evaluation activities.

Design and maintain Snowflake-based data platforms, cloud-native data lakes, and scalable ETL/ELT pipelines for asset-backed finance analytics. Orchestrate workflows with Dagster and AWS services, ensure data reconciliation and integrity, and support migration from legacy systems. Contribute to project planning, Jira backlog management, testing, cutover planning, and cross-functional go-live readiness.

Builds and maintains data pipelines and datasets supporting analytics, AI, and modeling. Responsibilities include ingesting healthcare claims and lab data into Snowflake and AWS Iceberg, processing structured and unstructured sources, curating data for AI use cases, implementing medallion architectures, evaluating data quality, and contributing to pilot initiatives using SQL, Python, AWS Glue, Terraform, and Snowflake.

Build and operate trusted finance data products, pipelines, models, reconciliations, dashboards, and automation. Partner with Finance, Accounting, Data Engineering, Product, and Platform teams to resolve data issues, improve reporting, support financial close, establish data lake quality controls, and enable timely insights. Use SQL, Python, dbt, Spark, Airflow, and AI-assisted tools to deliver tested, traceable, production-ready solutions.

Collects and analyzes data from project, financial, maintenance, and field systems; builds KPI dashboards and recurring reports; identifies trends, risks, and opportunities; supports budgeting and forecasting; validates data with project and operations teams; and communicates actionable insights to leadership while improving reporting processes.