Top Senior Data & Analytics Jobs in Tulsa, OK

Design, build, and operate large-scale data pipelines and ETL processes to normalize varied partner datasets. Lead technical decisions, mentor engineers, implement testing and monitoring, manage data warehouses/lakes, and collaborate cross-functionally to deliver robust data infrastructure that supports ML and product teams.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Senior Power BI developer responsible for building dashboards, scorecards, and analyses that deliver actionable insights. Partner with stakeholders and data architecture to join disparate datasets, ensure data quality, perform ETL, apply advanced DAX/Power Query and SQL, and present recommendations to senior leadership to drive KPI improvements.

Lead Tableau data visualization strategy: design and optimize high-performance dashboards, establish governance and best practices, mentor teams, enable adoption, and partner with data teams for robust models and performance.

Own pipeline reporting, revenue forecasting, pricing and deal-analysis frameworks, retention/renewal reporting, and marketing performance analysis. Create automated dashboards, partner with sales and engineering to maintain data pipelines, and present insights to commercial stakeholders to drive revenue growth.

Design, analyze, and document data products and technical specifications. Perform large-scale data profiling and SQL analysis, support data governance, partner with stakeholders to remediate issues, and help implement data quality, lineage, and ingestion standards.

Lead the RevOps analytics function: manage an analytics team, own revenue reporting and forecasting, build measurement frameworks, enforce data governance, partner with BI/engineering, analyze funnel and retention metrics, and embed AI/automation to improve revenue predictability and GTM performance.