Top Remote Data & Analytics Jobs in Tucson, AZ

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

Build and own the reporting and insight layer: write optimized Redshift queries, build dashboards, monitor model feedback signals, triage and prioritize investigations for data science, maintain ETL pipelines ingesting semi-structured data, and enable Customer Success with clear metrics and onboarding checks. Move into model validation and automation to scale analytic workflows.

The Business Analyst will gather requirements from clients, support project lifecycles, conduct demos, and manage change, while utilizing ServiceNow. Responsibilities include documentation and relationship building.

Lead and build Newfire's clinical data engineering practice: define architectures, reusable patterns, and governance; own analytics and transactional pipelines; provide hands-on technical leadership with Databricks/Snowflake/dbt; mentor and grow the team; partner commercially to identify opportunities; and integrate practical AI capabilities for healthcare data use cases.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

Manage the end-to-end data issue lifecycle for North America: intake, triage, root cause analysis, remediation planning and execution oversight. Produce IMR reporting and dashboards, maintain audit-ready records, engage stakeholders, and improve IMR processes and tooling to strengthen data quality and controls.

Own Mixpanel and partner closely with Product to turn product-level data into decision-grade insights. Define instrumentation and event taxonomy, build dashboards and notebooks, run cohort and retention analyses, design and analyze A/B tests, and collaborate with data engineers to model product event data. Document metrics, maintain a living glossary, and translate findings into actionable product recommendations.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.