Top Analytics Jobs in Phoenix, AZ

Lead a team supporting Epic analytics and clinical/operational systems. Oversee daily operations, project coordination, testing, reporting, data governance, staffing, training, and vendor interactions. Design scalable data models and pipelines (Microsoft Fabric, SQL Server, Power BI), ensure data quality, and present findings to executive stakeholders while maintaining system availability and compliance.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.

Lead and grow a BI and analytics team to build scalable, AI-enabled reporting and self-service analytics. Partner with cross-functional stakeholders to deliver executive dashboards, standardize metrics, ensure data quality and governance, and use AI tools to automate insights and accelerate dashboard development.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Design, build, and own Sardine's internal data platform and billing infrastructure. Implement and maintain ETL/ELT pipelines, warehouse partitioning, access controls, and data governance. Partner with stakeholders to define KPIs, produce dashboards, and ensure data quality for executive, GTM, product, and finance teams.

The Data and Analytics Consultant will design, develop, and implement data reporting, visualizations, and analytics solutions for clients while assisting them in data understanding and value extraction.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.

The Senior BI Analytics Engineer will design and deliver data models for analytics, ensuring data quality, and collaborating across teams to enhance AI-driven reporting and querying capabilities.

The Analytics Architect will design and implement cloud-based analytics solutions, maintain data pipelines, ensure data quality, and collaborate with teams to enhance operational efficiency.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

Build and maintain dbt data models, design BI dashboards and reports (Count and other tools), and deliver merchant/issuer analytics. Partner with GTM and product teams to translate data into actionable insights, improve data quality, and lead technical investigations to scale analytics infrastructure.

Lead full-stack analytics at Air by designing and maintaining dbt models and BigQuery transformation layer, ensuring data quality and observability, owning ingestion/orchestration, building self-serve BI (Mode/Hex) and AI-native interfaces, and partnering with product, growth, and GTM teams to deliver trusted data products and strategic insights.

The Enterprise Performance Analytics Engineer builds and maintains data pipelines and models, ensuring data quality and efficient reporting for analytics teams.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

As an Analytics Engineer at Axios, you'll design and maintain data products and visualizations, improving decision-making through actionable insights.

The Senior Data Scientist will lead revenue-driving initiatives, optimize strategies, enhance data analysis techniques, and improve data pipelines for maximum revenue impact.

Lead and scale the Data & Analytics Practice, drive AI-enabled data solutions, oversee client engagements, and mentor a high-performing team. Define growth strategies and modern data architectures while ensuring alignment with business outcomes and collaboration among stakeholders.

Lead and mentor a team of data analysts while remaining hands-on with SQL and BI tools. Partner with business leaders to translate goals into data requirements, deliver high-impact analyses and presentations, and recommend operational changes across marketing, call center, and clinical operations.

Lead measurement strategy for paid and performance marketing, design and interpret A/B and lift tests, run incrementality and attribution analyses, and optimize channel budgets. Build business cases, develop dashboards and BI workflows, evaluate AI-enabled analytics tooling, and enable self-serve analytics. Partner cross-functionally and present insights to leadership to drive experimentation, growth, and LTV outcomes.

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.

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

Implement and manage Adobe Analytics across web and mobile, define custom tracking, collaborate with dev and stakeholders, create reports and dashboards, support A/B testing and optimization, deliver insights and training to improve digital performance.

Lead Adobe Analytics architecture and MarTech ecosystem design, implement data layers and tagging across web and mobile, ensure QA and privacy compliance, enable reporting and audience activation, and drive cross-functional measurement and governance for personalization and optimization.