Top Data & Analytics Jobs in Spokane, WA

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Lead and architect high-value healthcare analytics engagements, build reusable analytic frameworks (DBT), partner with product and engineering, mentor analysts, ensure analytic quality, and represent Arcadia externally to drive population health and value-based care outcomes.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Support the Data Team with ad hoc analyses, SQL queries, dashboard maintenance, data quality, and AI-assisted analytics workflows. Prepare reports and presentations, document metrics and workflows, triage data requests via Jira, and help maintain data integrity across BI tools for internal stakeholders.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

Lead advanced analytics for countrywide insurance product programs: build dashboards and monitoring frameworks, conduct deep-dive analyses and predictive modeling, identify systemic process and data gaps, partner with product and cross-functional teams, and influence strategic decisions to improve growth, retention, and profitability.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.