Top Remote Analysis Reporting Jobs in Tucson, AZ

Leads healthcare quality analytics using hospital performance, national rankings, Medicare claims, and CMS data. Replicates quality methodologies, identifies improvement opportunities, builds dashboards and benchmarking tools, and establishes analytic validation standards. Presents insights to executives and customers, supports pre-sales and engagements, partners with data scientists and consultants, and mentors analysts.

Owns enterprise data architecture for Raytheon’s SAP ECC-to-S/4HANA transformation. Designs canonical data models, integration patterns, bridge reporting, semantic layers, and cross-system analytics for finance, supply chain, and other domains. Guides SAP Analytics Cloud, Snowflake, Business Data Cloud, and BODS solutions; establishes governance, standards, lineage, and observability. Creates TOGAF-aligned architecture artifacts, reviews delivery solutions, and coaches technical teams throughout the migration lifecycle.

Designs, develops, tests, and executes SQL-based data migrations and integrations for higher education Advancement systems. Builds data pipelines, staging tables, transformation logic, stored procedures, validation processes, and database-driven integrations connecting legacy platforms, institutional databases, and Salesforce. Configures Salesforce, troubleshoots data and performance issues, supports migration testing and deployments, and collaborates with architects, consultants, and client stakeholders. Periodic travel and client relationship development are required.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

Analyze marketing performance and ROI across markets, identify expansion opportunities, evaluate market saturation and competition, and support investment decisions. The role requires advanced SQL, funnel analysis, dashboard development, multi-source data integration, statistical reasoning, and clear communication of recommendations to marketing and leadership. The analyst will also use AI tools such as Claude and partner with data engineering to improve data quality and decision support.

Design, build, and deploy production-grade data pipelines, analytics platforms, and Generative AI applications on Databricks. Lead enterprise migrations from legacy data platforms, architect cloud-native solutions, implement RAG and ML pipelines, and advise executive client stakeholders. Drive Databricks adoption and account growth by identifying new use cases, while mentoring engineers and contributing reusable delivery accelerators.

Reviews and compares AI chatbot responses using predefined criteria for accuracy, relevance, completeness, clarity, consistency, and quality. Documents evaluation guidelines, analyzes workflows and data, identifies recurring issues, prepares reports, tracks quality metrics, and collaborates with project teams. This fully remote, 16-week contract requires 8 hours per day, five days per week, with Pacific Time overlap and possible weekend work.

Leads the architecture and evolution of scalable data platforms, pipelines, and data products across multiple teams. Designs Snowflake and cloud-based solutions for batch, streaming, CDC, ingestion, transformation, orchestration, and data delivery. Establishes engineering standards, governance, observability, testing, CI/CD, and reliability practices; mentors engineers; guides architecture and roadmap decisions; resolves complex incidents; and evaluates AI, automation, and MCP-enabled data capabilities.

Own analytics as an internal data product across GTM, People, Finance, and related functions. Translate ambiguous business questions into self-service data solutions, deliver executive-ready narratives, manage stakeholder priorities, and guide data-driven decisions. Serve as a marketing analytics subject matter expert across attribution, campaign measurement, lead tracking, funnel analysis, predictive modeling, and experimentation. Use SQL, modern data-stack tools, BI platforms, and AI-assisted modeling to deliver actionable insights.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.