Top Data & Analytics Jobs in Spokane, WA

Designs and maintains scalable cloud data architectures, pipelines, ETL processes, data warehouses, databases, and data models. Ensures data quality, accuracy, security, availability, and consistency across sources. Develops SQL queries for analytics and reporting, and documents pipelines, schemas, architectures, and models. The role requires expertise with Python, Java, Scala, R, SQL, relational and NoSQL databases, cloud platforms, and Snowflake.

Leads the design and delivery of scalable analytics solutions using Azure Databricks, Power BI, and related platforms. Transforms and validates structured and unstructured data, applies statistical techniques, develops dashboards and analytical models, and implements data governance and quality processes. Partners with business and technology stakeholders to translate requirements into technical solutions, provides peer guidance, monitors data trends, and communicates actionable insights to technical and non-technical audiences.

Partners with live music venue operations and hospitality leaders to deliver business intelligence, dashboards, reporting, pricing strategies, guest insights, and cost-management analysis. Supports monthly and post-event reviews, data integrity, innovation, and operational excellence initiatives. Builds relationships with clients and stakeholders, experiments with process improvements, and serves as a subject-matter expert for live music programming.

Designs and maintains pipelines migrating financial data from legacy Oracle databases to Oracle ERP. Develops SQL and PL/SQL transformations, backend integrations, data mappings, reconciliation, testing, monitoring, troubleshooting, and documentation. Partners with accounting, business, and technical stakeholders to resolve issues and support large-scale financial transformation. The role also involves AI tool adoption, code reviews, solution design, deployment activities, governance, communication, mentoring, and project oversight.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

Lead data architecture consulting engagements, pursuit teams, client workshops, proofs of concept, and complex solution delivery. Design modern data architectures, integrate third-party platforms, create implementation roadmaps, and translate technical concepts for executive and technical audiences. Manage globally distributed teams, provide mentorship and thought leadership, support sales pursuits, and advise clients on data governance, quality, cataloging, lineage, master data management, cloud platforms, modernization, scalability, security, and AI-enabled solutions.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.

Lead the firm’s analytics strategy, roadmap, and growing analyst team. Partner with executives and law firm operations leaders to define KPIs, evaluate performance, identify bottlenecks, build forecasting and predictive capabilities, and translate data into business actions. Guide SQL, Python/R, statistical modeling, visualization, data quality, and analytics infrastructure standards while partnering with technology and data engineering teams to embed insights into operational workflows.

Own end-to-end marketing measurement from campaign tracking through pipeline and revenue. Define tagging, event tracking, dataLayer, UTM, taxonomy, CRM, and marketing automation standards; ensure clean data handoffs, routing, attribution, and reporting. Lead QA and troubleshoot discrepancies across technical and operational systems. Partner with marketing, sales, analytics, engineering, and operations teams to establish measurement frameworks, documentation, data models, and repeatable processes leadership can trust.