Top Business Intelligence Jobs in Tucson, AZ

Design and build PerfectServe’s unified cloud data platform, including ingestion pipelines, integrations, data models, metrics, and consumer-facing data layers. Establish architecture, engineering, quality, and testing standards; enable safe extraction from production systems; partner with data users; and mentor data engineers. The role requires substantial cloud data platform experience, deep SQL, warehouse expertise, ELT, change-data-capture, AWS, modeling, orchestration, and data quality skills.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Leads the Sales Analytics and Reporting function and manages Sales Analysts. Oversees dashboards, scorecards, KPI tracking, profitability analysis, business insights, executive reporting, and sales technology platforms. Partners with Sales, Finance, Product, Technology, and other stakeholders to improve performance, profitability, planning, and decision-making. Develops team capability, reporting processes, platform adoption, and analytical effectiveness while translating complex data into actionable recommendations.

Develop and deploy business intelligence applications for a U.S. Air Force financial platform across development, testing, integration, and production environments. Design and optimize Informatica ETL pipelines, Oracle databases, SQL and PL/SQL processes, data warehouses, BI semantic layers, and SAP integrations. Support Agile delivery, budgeting integrations, monitoring, interface changes, and security hardening. The role also requires Oracle APEX, WebLogic, HTTP Server, performance tuning, and collaboration on data-related issues.

Lead CX data intelligence initiatives using SQL, dashboards, analytical models, and AI/LLM techniques. Analyze customer journeys, operational metrics, churn risks, and retention indicators; develop insight agents and self-service reporting; define CX health metrics; and translate findings into strategic recommendations, process improvements, and experiments. Partner with operations, support, product, data, and engineering teams while maintaining data quality, governance, and documentation.

Designs, builds, and maintains scalable data pipelines, workflows, analytics solutions, and AI/ML capabilities within Palantir Foundry. Models enterprise data using Foundry Ontology, manages data assets and governance, integrates analytics tools, troubleshoots platform issues, and translates stakeholder requirements into maintainable solutions. The role also supports FAA users through documentation, training, collaboration, and ongoing platform enhancement.

Leads the vision, architecture, strategy, and execution of enterprise data platforms supporting scalable analytics and AI initiatives. Oversees modern data technologies, production reliability, FinOps, governance, architecture standards, and cross-functional delivery. Builds and mentors engineering teams, communicates with executives, evaluates third-party technologies, resolves critical production issues, and drives continuous improvement. The role is remote with occasional planned travel to the Southfield, Michigan office.

Owns and leads commercial master data management across HCP, HCO, payer, patient, product, and organizational domains. Establishes governance frameworks, stewardship programs, data quality standards, matching and survivorship rules, and trusted golden records. Manages commercial data platforms, integrations, analytics datasets, releases, vendors, and offshore teams. Writes SQL, builds validations and data pipelines, troubleshoots integrations, supports commercial launches, and drives operational improvements across pharmaceutical commercial systems.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

Analyze insurance product and portfolio performance, build dashboards and reporting tools, validate data, and translate complex insurance questions into actionable recommendations. The role supports rate revisions, state expansion, product development, and profitable growth while partnering with Product, Engineering, Data, Underwriting, Compliance, and other teams. It also uses SQL, business intelligence platforms, and AI tools such as Claude to improve workflows and decision-making.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Build and scale business intelligence solutions that automate processes, integrate and transform data, and deliver actionable visualizations. Partner with business stakeholders to define requirements, develop Databricks workflows and pipelines using SQL and PySpark, collaborate with technology and data science teams, lead project deliverables, and mentor junior team members.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, reporting platforms, and dashboards. The role uses SQL, Python, Tableau, cloud platforms, and distributed data technologies to deliver self-service analytics, validate data quality, optimize pipeline performance, and support reliable data systems. Responsibilities include stakeholder collaboration, requirements gathering, KPI visualization, technical documentation, operational monitoring, and mentoring junior engineers and analysts.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Develop and maintain BI reports and dashboards for the Mortgage Lending Division. Analyze large datasets, identify trends, validate reportable data, and support regulatory reporting such as HMDA and Fair Lending Analysis. Collaborate with business teams to gather requirements, automate reporting processes, document data definitions, and provide training on reporting tools. The role also supports data dictionaries, exception reporting, and operational improvements.

Develop and maintain Power BI, SSRS, SQL, recurring, and ad hoc reports for the Mortgage Lending Division. Analyze large datasets, validate regulatory reporting data, identify trends, automate reporting, and provide actionable insights. Collaborate with business units, support HMDA and fair lending reporting, document data dictionaries and procedures, and train users on reporting tools.

Leads a client’s migration from SQL Server, SSIS, and SSRS to Snowflake and Sigma while maintaining legacy reporting operations. Designs data models, ETL pipelines, reports, dashboards, source-to-target mappings, and migration plans; validates reporting parity and coordinates phased cutovers. The role also provides client-facing technical leadership, troubleshooting, documentation, peer reviews, and ongoing support for banking data and reporting systems.

Designs and maintains data warehouse infrastructure, semantic and dimensional models, metrics layers, dashboards, reporting, and secure data pipelines. Builds governed self-service analytics in Sigma, Power BI, and Databricks; defines KPIs and data standards; implements row-level security and Entra ID controls; supports data quality, observability, AI/ML use cases, and BI adoption. Collaborates with technical and business stakeholders in an Agile-Scrum environment.

Lead ownership of BI reporting infrastructure: build and standardize dashboards, extract insights from messy third‑party data, partner with marketing teams to drive performance optimization and deliver proactive retrospective analyses that influence business decisions.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Develop and maintain Microsoft Power Apps and Power BI solutions for federal customers. Build data models, DAX measures, Power Query transformations, dashboards, reports, gateway connections, scheduled refreshes, and security controls. Integrate SQL Server and external data sources, perform data quality analysis, support accessibility and ATO compliance, and collaborate with product owners and technical teams in Agile ceremonies. Document solutions, manage artifacts with Git, and translate business requirements into actionable applications and reporting.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

Leads enterprise business intelligence and analytics across multiple divisions and locations. Establishes governed KPI definitions, reporting architecture, financial and operational analytics, semantic models, data-quality practices, and self-service reporting. Partners with FP&A, IT, Finance, and Operations to align analytics with financial results, guide technical delivery, evaluate BI platforms, and support forecasting and performance improvement. Directs internal or external development teams and communicates actionable insights to executives and operating leaders.

Supports the Mortgage Lending Division by producing and maintaining routine reports, dashboards, data extracts, and basic analyses. Validates data accuracy, automates reporting where appropriate, documents procedures, investigates trends and audit issues, and responds to operational reporting needs. The role involves learning internal systems, metrics, and business processes while collaborating with stakeholders. Candidates should have basic Excel and data visualization skills, foundational SQL knowledge, strong analytical abilities, and zero to two years of relevant experience.