Top Remote Data & Analytics Jobs in Tucson, AZ

Transforms data into actionable insights for CVS Health’s Direct-to-Consumer channels. Develops reporting solutions, quality dashboards, and analytics on agent behavior, quality trends, and process opportunities. Partners with Quality Assurance, Compliance, Operations, and Vendor Management to ensure data integrity and improve performance. Supports vendor oversight, internal reporting, and quality-monitoring innovation using tools such as Excel, SQL, and NICE CXone, with a focus on Medicare sales processes.

Own and evolve Looker as the company-wide business intelligence platform. Build dashboards, data models, pipelines, and integrations connecting Snowflake and other sources. Ensure data quality and provenance, support operational reporting, and partner with Finance, Data Science, and business teams. Help develop AI- and LLM-based agentic reporting tools that enable self-service analytics. Communicate technical concepts across the organization and provide insights for operational decision-making.

An 11-week paid actuarial internship supporting product development, financial management, risk management, and actuarial analytics. Responsibilities include compiling and validating data, conducting actuarial studies and experience analyses, performing calculations and reserve analyses, preparing financial projections and management reports, documenting methodologies and assumptions, and collaborating with business partners. Interns also receive mentorship, technology training, leadership exposure, and presentation-development opportunities.

Designs and maintains scalable data architecture, Snowflake warehouses, ETL/ELT pipelines, dimensional data models, and governance processes. Partners with business stakeholders to deliver insights for pricing, inventory, customer segmentation, and marketing optimization. Builds reliable analytics datasets and dashboards, integrates data tools, monitors data quality, and ensures compliance within the regulated cannabis industry.

Maintains accurate, consistent data across Microsoft Dynamics and other company systems. Performs data entry, QA/QC audits, discrepancy resolution, duplicate record cleanup, data governance, documentation, and process improvement. Serves as the organization-wide contact for data entry needs and collaborates with multiple departments to establish standards, improve workflows, and support reliable reporting and operations.

Designs and builds production data systems, pipelines, database schemas, analytical models, and internal platforms. Responsibilities include writing tested code, optimizing queries and storage, controlling infrastructure costs, enforcing CI/CD, and implementing data testing, monitoring, and alerting. The role also develops AI and LLM-backed data use cases, including retrieval pipelines, embeddings, vector storage, evaluation harnesses, and agentic workflows.

Analyzes complex datasets to uncover business insights, develops dashboards and reports using SQL and visualization tools, and presents recommendations to stakeholders. Partners with engineering, operations, and other teams to solve business problems, prioritize strategy and projects, manage deliverables, and ensure data accuracy and timeliness.

Develop and own healthcare-related data analyses, financial models, databases, and data resources. Write Python and SQL code, validate results, perform data quality audits, identify anomalies, and maintain data integrity. Create reports, presentations, diagrams, and engineering requirements documents, while partnering with strategy leads and cross-functional stakeholders to design data-informed technology solutions. Support client projects, communicate findings, and ensure accurate, compliant deliverables.

Build and maintain ETL and data pipelines using Python, PySpark, and AWS services. Orchestrate workflows, develop event-driven integrations, optimize data storage and queries, process API and JSON data, and implement data quality monitoring. Support CI/CD, production operations, cloud migration, data lake and lakehouse initiatives, and near-real-time systems while collaborating with stakeholders to deliver technical solutions.

Designs and governs PANTHERx’s semantic layer on Databricks, including Unity Catalog metric views, Gold-layer tables, promotion logic, and reusable data products. Establishes canonical, versioned business metrics for BI, analytics, partner feeds, and AI inputs. Responsibilities include data modeling, migration, validation, observability, documentation, governance, stakeholder collaboration, and mentoring analytics engineers. The role requires advanced SQL, Python, and PySpark skills, strong Databricks expertise, and experience operating across analytics engineering and data engineering.