Top Remote Data & Analytics Jobs in Spokane, WA

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.

As the Client Insights Lead Analyst, you will create analytics strategies, lead data analysis, collaborate with teams, and communicate insights to clients effectively.

Own and improve the dbt modeling and semantic layers, implement CI/CD, tests, observability, and governance; build governed metrics for BI and AI consumption; partner with Data Engineering and Risk to stabilize pipelines and improve data quality and documentation.

Lead enterprise data strategy and governance engagements; advise C-suite clients; design governance frameworks (MDM, metadata, data quality, access controls); oversee delivery, mentor leaders, drive business development and thought leadership; align modern data stack to business outcomes.

The Product Analyst will analyze product performance, manage workloads, document processes, support product reviews, and generate reports while collaborating with teams.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Senior individual contributor in People Analytics leading workforce analysis, dashboards, data quality, and insight generation to inform HR and business decisions. Partners with talent, engagement, and planning teams to produce scalable analytics, benchmarks, and recommendations.

Own and build reliable analytics data products: define metrics, create and maintain dbt models, design dashboards for growth/finance/ops, improve data quality via testing and monitoring, and enable self-serve analytics for stakeholders.

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.

The analyst will perform advanced credit risk analysis, monitor performances, provide guidance on data analysis, and ensure compliance with regulations.

Design, build, and maintain Databricks-based data pipelines and ETL/ELT processes using Python and SQL. Optimize workflows for performance and cost, support data modeling and cloud integrations (Azure/AWS/GCP), monitor and troubleshoot pipelines, document best practices, and collaborate with cross-functional teams.