Top Analysis Reporting Jobs in Spokane, WA

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Analyzes healthcare claims, provider reimbursement, QPA, and dispute data to support No Surprises Act negotiations, arbitration, and OON liability management. Builds SQL-based reports, dashboards, data processes, and financial views; validates data quality; tracks dispute KPIs; integrates internal and external sources; and presents actionable recommendations to leadership and cross-functional stakeholders.

Leads enterprise data platform architecture, engineering standards, technical decisions, and development of scalable data products. Designs batch and streaming systems, governance, observability, security, and reliability practices. Partners cross-functionally, mentors engineers, drives modernization and migrations, and establishes reusable patterns for data modeling, orchestration, quality, and platform operations.

Leads Relation Insurance’s enterprise data engineering and analytics function, owning data strategy, architecture, pipelines, governance, quality, reporting, and AI-enabled workflows. The role requires hands-on development in SQL, Python, and PySpark, executive communication, technical team leadership, lakehouse architecture, Power BI modeling, production support, and secure data management. The director also directs AI coding agents, builds LLM-powered workflows, establishes engineering standards, and delivers reliable data products aligned with business priorities.

Collects, processes, and analyzes data from multiple sources using R, Python, and SQL. Develops reports, visualizations, analytical methods, and data-driven insights while applying statistical and introductory machine learning techniques. Collaborates with internal and external stakeholders, documents project progress in JIRA, debugs code, clarifies requirements, and communicates findings through reports and presentations.

Leads and develops a data engineering team implementing Navigate360 integrations for partner campuses. Oversees integration design, data mapping, validation, reconciliation, quality controls, delivery planning, and scalable implementation processes. Partners with Product, Launch, and Partner Success teams to resolve technical and partner challenges, improve adoption, manage project health, and ensure reliable outcomes. Provides technical mentorship, code and design review, stakeholder communication, and continuous process improvement.

Administer Oracle, SQL Server, and MySQL databases in a fully remote federal environment. Responsibilities include installation, configuration, monitoring, performance tuning, patching, security, backup and recovery, vulnerability remediation, incident response, documentation, compliance, and application deployment support. The role requires collaboration with development and hosting teams, occasional travel, and after-hours or on-call availability. A Public Trust clearance must be obtainable.

Build and operate trusted finance data products, pipelines, models, reconciliations, dashboards, and automation. Partner with Finance, Accounting, Data Engineering, Product, and Platform teams to resolve data issues, improve reporting, support financial close, establish data lake quality controls, and enable timely insights. Use SQL, Python, dbt, Spark, Airflow, and AI-assisted tools to deliver tested, traceable, production-ready solutions.

Collects and analyzes data from project, financial, maintenance, and field systems; builds KPI dashboards and recurring reports; identifies trends, risks, and opportunities; supports budgeting and forecasting; validates data with project and operations teams; and communicates actionable insights to leadership while improving reporting processes.

Build and maintain product data models, ELT pipelines, semantic layers, and self-service analytics assets. Partner with Product Engineering and Data Governance to define canonical data, certify metrics, document taxonomies, monitor data quality, and support expansion and upsell analytics. Translate business requirements into governed data products, communicate insights to technical and non-technical stakeholders, and ensure data tooling complies with federal frameworks including FedRAMP and DoD IL4/5.