Top Senior Analysis Reporting Jobs in Tucson, AZ

Analyze healthcare claims and clinical data to build data models, analytical pipelines, predictive and risk-model inputs, dashboards, scorecards, and reusable analytics assets. Translate ambiguous customer and clinical questions into actionable data plans, manage delivery across stakeholders, present findings to customers, maintain quality standards, mentor junior analysts, and contribute to analytics roadmaps, automation, and scalable methodologies.

Lead global Customer Success analytics strategy, architect data and health/adoption models, oversee data pipelines, deliver executive-level storytelling, mentor an analytics team, and drive cross-functional KPI alignment and self-serve BI adoption.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Design, build, and operate scalable data pipelines and integrations for an RCT-driven voter platform. Extend data platform, optimize cost and reliability for election-scale loads, lead cross-system projects, ensure data quality, document systems, and participate in on-call incident response.

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.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Lead martech data strategy and governance to enable accurate, accessible customer data for segmentation, identity resolution, integrations, and personalized campaign activation across marketing platforms. Partner with Technology, Data & Analytics, Compliance, and business stakeholders to define requirements, drive data quality, and modernize platform integrations.

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.