Top Remote Data & Analytics Jobs in Phoenix, AZ

Leads enterprise data architecture strategy, including data warehouses, lakehouses, Data Mesh, integration patterns, streaming, AI readiness, data governance, and Master Data Management. Establishes standards for pipelines, transformations, lineage, data contracts, and data products while advising business units and mentoring data engineering, BI, and MDM teams. The remote U.S. role requires occasional travel to Nashville and extensive experience with cloud data platforms and modern data engineering technologies.

Supports cross-functional manufacturing, finance, engineering, IT, and operations initiatives through data consolidation, business analysis, KPI reporting, requirements gathering, and cost-benefit analysis. The role develops recommendations, project status reports, presentations, and post-project audits while helping support strategic decisions and operating effectiveness. This position is remote within specified states and requires up to 25% travel.

Leads the data engineering organization and enterprise Databricks Lakehouse on AWS. Owns team development, platform strategy, delivery, reliability, governance, budget, vendors, architecture standards, and regulatory compliance. Partners with executives on data transformation, MDM, ERP migration, analytics, and AI enablement. Requires extensive data engineering leadership, Databricks and AWS expertise, regulated-environment experience, and proven budget and vendor management.

Manage Oracle and PostgreSQL databases across on-premises and AWS environments, including upgrades, migrations, performance tuning, security, and backup recovery. Design and maintain ETL pipelines using Talend, SQL, Power Automate, and related tools. Perform data profiling, quality analysis, governance, and cloud migration activities. Create technical architecture and lineage documentation while supporting regulated, audit-ready data platforms and integrations.

Lead the architecture, design, development, troubleshooting, and optimization of Snowflake data solutions for higher education clients. Conduct discovery and design workshops, assess existing environments, create enterprise data models and future-state architectures, develop ETL/ELT pipelines, implement security and data-quality controls, and optimize performance and costs. Serve as a client-facing technical advisor, translate business requirements into scalable solutions, lead technical workstreams, support business development, mentor teams, and travel periodically.

Own customer data migration projects from analysis and cleanup through execution, validation, and communication of results. Develop and maintain migration scripts and tooling, work with APIs and structured data, resolve quality issues, and collaborate with Customer Success, Support, Product, and Engineering. Manage multiple projects, handle complex datasets, answer customer questions, safeguard sensitive information, and improve migration processes, documentation, and scalability.

Leads analytics engineering and analytics-ready data architecture for government clients. Designs standardized data models, transformation logic, validation frameworks, and reusable integration patterns. Governs data quality, QA, backfills, and release processes while resolving complex data issues. Integrates web, email, social, survey, and client-system data to support dashboards, reporting, measurement, and insights. Advises stakeholders, influences enterprise standards, coordinates with product teams, and supports client-facing analytics workstreams.

Own measurement strategies for large omnichannel brands, including test design, marketing mix modeling, incrementality analysis, attribution interpretation, and budget recommendations. Translate complex findings into actionable guidance for executives and marketing teams, support prospect conversations, identify customer and product gaps, and collaborate with Product, Data Science, and Customer Success. The role requires strong paid media expertise, omnichannel fluency, statistical measurement literacy, and the ability to communicate uncertainty and recommendations clearly.

Build and operate reliable ETL and ELT pipelines across lakehouse and transactional systems. Develop data models, enforce governance, integrate diverse data sources, and support analytics, APIs, and predictive tools. Monitor performance, data quality, lineage, cost, and uptime while collaborating with data science, AI, product, and innovation teams.

Lead enterprise adoption and toolchain integration for business analysis across federated teams. Design enablement curriculum, integrate standards and AI-enabled tooling (Azure DevOps, ServiceNow, Nexus, Power BI), build decision-oriented dashboards and leading indicators, drive adoption and governance, surface portfolio trends, and partner with stakeholders to improve delivery predictability and compliance.