Top Senior Data & Analytics Jobs in Tucson, AZ

Lead design and governance of enterprise Master Data Management using Stibo/MDM platforms. Define canonical data models, integration patterns (API/event-driven), match & merge and survivorship strategies, stewardship workflows, data quality and lineage, RBAC, and scale multi-domain MDM across Product, Customer, and Supplier domains while aligning with enterprise data governance and cloud platforms.

Design, maintain, and automate GTM business data models, ensure data quality and observability, build BI-as-code pipelines (CI/CD, Git), create visualizations, and partner with Sales, Marketing, Finance, and Product to enable reliable reporting, analytics, and AI capabilities.

Lead analytics strategy for client accounts: create measurement plans, testing roadmaps, and cross-channel analyses. Use BI tools and SQL to connect data, generate insights, and present clear, actionable recommendations to clients and internal teams.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

Serve as a senior advisor on enterprise data architecture and Adobe Experience Platform. Lead client discovery, design XDM schemas and identity resolution, guide data ingestion/ETL, governance, and Customer 360 initiatives. Provide technical leadership, mentor teams, review architecture, and contribute templates and best practices across consulting engagements.

Lead data management and quality efforts, consult with stakeholders and vendors, design processes and solutions, perform root-cause analysis of complex data errors, implement improvements, integrate technologies, validate deliverables, and present recommendations to senior management to enable AI-ready data and BI solutions.

Build and maintain scalable ETL/data pipelines and internal frameworks to support ML and product teams. Drive architecture, observability, data quality, and engineering best practices across AI/ML workflows and prompt-engineering pipelines.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Client-facing BI consultant responsible for end-to-end delivery of TARGIT-based analytics: requirements gathering, prototyping, backend work, dashboards, training, deployment, optimization, and customer engagement.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.