Top Data & Analytics Jobs in Spokane, WA

Provide technical and administrative support to leadership: monitor sprints and Scrum synchronizations, perform technical research, write Python scripts for automation and API testing, manage and report data using advanced Excel, and prepare meeting summaries and cross-functional coordination.

Lead analytics and insights for the CFO and exec team: produce executive-ready analyses, design scalable analytics infrastructure, leverage AI to accelerate workflows, partner cross-functionally to drive strategy and execution, and manage multiple high-impact initiatives.

Lead data product strategy and governance for customer-facing reporting within Managed Services. Own reporting product roadmap, data quality, standards, delivery platforms (Redwood Insights, BI, Snowflake, Excel), implementation readiness, and cross-functional alignment to scale trusted, automated customer analytics and reduce manual reporting.

Lead analytics strategy for federal programs: perform statistical modeling, forecasting, and data mining; build dashboards and automated workflows; ensure NIST/FISMA compliance and data quality; present findings to government stakeholders; mentor junior analysts and manage analytics workstreams.

The Technical Enablement & Documentation Lead is responsible for developing and maintaining product documentation, creating a certification program, and collaborating with teams to improve the knowledge experience for Flosum's users.

As a Curriculum Manager, you'll create and manage cloud education content, collaborating with experts, utilizing AI tools, and addressing curriculum gaps.

Own product telemetry, maintain dbt models in Snowflake, support self-service reporting and NLP queries, drive product insights from user and retention data, and monitor Airbyte syncs to ensure data quality.

Design and own end-to-end data platform architecture, build ingestion and transformation pipelines, model multi-tenant datasets, optimize Postgres and ClickHouse performance/cost, implement orchestration and observability, define data quality and reconciliation standards, and mentor data/product engineers.

Ensure engineering teams build the right work by producing high-quality context, maintaining AI-driven documentation, writing and validating SQL analyses and recurring reports, prototyping proofs-of-concept, and capturing acceptance criteria, edge cases, and measurable outcomes.

Embed with a single enterprise client to build and edit SQL for audience building and campaigns, design scalable data models, clean and automate pipelines, investigate data discrepancies, and improve workflows to support fast weekly delivery cycles.