Top Senior Analytics Jobs in Phoenix, AZ

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Design and build Toast’s enterprise analytics layer and AI-ready semantic layer in the data warehouse. Collaborate with domain teams and data engineering to implement hub-and-spoke architecture, define complex business logic in SQL, support scalability, partner with stakeholders, and provide technical mentorship.

Lead retail analytics to identify growth and efficiency opportunities, build strategic recommendations (store footprint, pricing, omnichannel), conduct market/competitive research, drive cross-functional initiatives, and deliver executive-ready analyses and frameworks to inform retail and digital strategy.

Lead building a data- and AI-enabled growth engine to improve pipeline quality and visibility. Define data governance, segmentation, scoring, and KPIs; operationalize demand-generation campaigns and tooling; prototype AI-driven automation and reporting; partner with vendors and sales/marketing to measure and improve pipeline conversion and ROI.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead client-facing marketing analytics projects (MMM, attribution, digital analytics, pricing, forecasting). Provide analyses, recommendations and presentations; manage and grow a team; travel extensively.

Lead and grow the customer analytics practice for Communications, Media & Technology clients. Define analytics strategy and thought leadership, deliver large-scale client engagements, and oversee CRM modeling, reporting, and predictive analytics to drive client outcomes.

Lead end-to-end data analysis and decision science for P&C underwriting. Acquire, integrate, and analyze complex and emerging datasets, build statistical and prescriptive models, produce visualizations and clear recommendations for business leaders, and support operationalizing strategies to improve risk selection and profitability.

Design, build, and maintain dashboards and reporting tools; analyze large datasets to identify trends and anomalies; validate data accuracy; translate business questions into analytics; present findings and recommendations to stakeholders; collaborate with IT to improve data infrastructure and automate reporting processes.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Lead end-to-end customer experience analytics: translate business questions, build/validate datasets, perform root-cause and impact analyses, influence stakeholders, and track post-implementation results. Partner cross-functionally, manage multiple projects, and communicate insights to senior leaders.

Lead analytics for ancillary products by designing and implementing analyses, automating reporting, and developing data-driven product and process improvements. Work with stakeholders to produce insights and visualizations (Tableau), manipulate large datasets using SQL/Snowflake/R and Excel, and communicate recommendations to senior leadership.

Lead portfolio analytics for Amazon Credit & Payments: define problems, source and analyze data, build dashboards, measure and optimize lifecycle and campaign performance, partner cross-functionally, and coach analytics teams to drive growth, profitability, and improved customer experience.

The Analytics Manager will lead analytics for the Payments and Identity lifecycle, manage a team of analysts, develop KPIs, and ensure data quality while collaborating with cross-functional teams.

Lead development and delivery of reporting, dashboards, and analytics for Direct-to-Consumer channels to monitor agent behavior, quality performance, and process improvements. Collaborate with Quality Assurance, Compliance, Operations, and Vendor Management to ensure data integrity, support vendor oversight, and integrate data tools into quality monitoring.

Lead pricing strategy and origination risk analytics to optimize loan pricing, forecasting, and approval frameworks. Manage and mentor analysts, build quantitative models, integrate third-party data, run experiments, and present recommendations to senior leadership to drive growth and profitability.

Use data analytics to identify and reduce operational risk across EP & TBM. Analyze large datasets, perform root cause analysis, recommend scalable process improvements, build dashboards and visualizations, measure initiative effectiveness, automate reporting, and partner with engineering, product, and risk teams to prioritize and implement risk reduction.

Lead analytics projects for Personal Wealth Marketing: translate business needs into analyses, integrate and analyze data, run regression and experimentation, build dashboards and presentations, and partner cross-functionally to drive marketing strategy and adoption.

Support enterprise data governance by documenting end-to-end data lineage, designing ADS components, building GCP data pipelines and data quality controls, contributing to data modeling and target-state design, and acting as a bridge between engineering, enterprise architecture, and business stakeholders while presenting findings to senior leadership.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead digital analytics strategy and a team to deliver member insights across digital touchpoints. Drive data governance, analytics platform delivery, reporting modernization, experimentation, and strategic recommendations to senior stakeholders to improve digital experience and business outcomes.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

Lead delivery pods for enterprise data governance and ADS architecture: design target-state ADS, document data lineage, implement aggregation-layer controls, conduct SME interviews, translate policy into delivery plans, manage analysts, select governance tooling, and report KPIs to senior stakeholders.

Lead development of Marriott's cloud data platform, build and own large-scale ETL pipelines on AWS and Snowflake, mentor engineers, manage service provider deliverables, ensure governance, data quality, deployment and production support, and research emerging AI/ML capabilities.