Top Analysis Reporting Jobs in Tulsa, OK

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead measurement strategy for a book of clients, designing statistical models (MMM), experiments (MMT), and customer analyses. Use R, Python, SQL and ETL tools to extract insights, present advanced methodologies to stakeholders, provide strategic recommendations tied to business goals, mentor measurement analysts, drive process efficiencies, and leverage proprietary Nova tools and AI to optimize deliverables.

Supports business development through market intelligence, industry and competitive research, project opportunity tracking, stakeholder identification, account research, reporting, dashboard preparation, CRM and database maintenance, and process improvement. The role focuses primarily on data center infrastructure while supporting additional strategic markets. It transforms research and market data into actionable insights for account executives, pursuit strategies, and revenue growth.

Lead design, development, and migration of enterprise data warehouse solutions from SAP BW/BW4HANA to SAP Datasphere. Architect data models and hybrid data flows with Microsoft Fabric/Azure Synapse, integrate BW with Salesforce and SQL Server, embed AI capabilities (Copilot, Azure OpenAI), manage offshore teams, enforce standards, and deliver Power BI reporting and analytics to business stakeholders.

Lead design, development, and migration of enterprise SAP BW solutions to SAP Datasphere; architect hybrid data flows with Microsoft Fabric and Azure Synapse; integrate BW with Salesforce and SQL Server; embed AI (Copilot, Azure OpenAI) into analytics; manage deliverables, mentor offshore teams, enforce standards, and ensure data integrity and performance for reporting and analytics.

Maintain and monitor Snowflake data warehouse and ingestion pipelines. Troubleshoot file/load/data quality issues, operate SFTP/drop-zone/file automation, support scheduled loads, build dbt models and tables, document runbooks, and serve as backup for core warehouse operations while collaborating with engineering and IT.

Lead development of enterprise data and analytics systems using Snowflake and Python. Build and optimize data pipelines on AWS (Lambda, Step Functions, ECS), write advanced SQL, and apply domain knowledge of asset management and financial markets.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Leads and develops a data engineering team implementing data integrations for partner campuses. Owns implementation approaches, scalable delivery processes, data mapping, validation, reconciliation, quality controls, project health, and capacity planning. Partners with Product, Launch, and Partner Success teams to resolve technical and partner challenges, improve integrations, and support adoption. Provides technical mentorship, design and code reviews, stakeholder communication, and continuous process improvement.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.