Top Senior Analysis Reporting Jobs in Portland, OR

Design, build, and maintain scalable data lakehouse platforms and ELT pipelines. Improve engineering practices, develop automation/tooling, monitor performance, reduce costs, and support platform modernization across Azure and cloud data technologies.

Lead end-to-end digital analytics across websites, products, and campaigns: implement and govern event and conversion tracking, ensure data integrity, build dashboards, connect campaign and CRM data to full-funnel outcomes, generate actionable insights, and support AI-enabled reporting and experimentation to improve conversion and user experience.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Support definition, validation, testing, and stabilization of mission-critical data integrations and interfaces across source systems, staging, transformation layers, and reporting platforms. Perform source-to-target validation, reconciliations, interface testing, cutover readiness, production stabilization, issue triage, and documentation to ensure accurate federal financial reporting.

Senior BI/reporting role focused on LTSS & Dual Eligible programs. Develop ETL pipelines, complex reports, and interactive Power BI/Tableau dashboards; perform advanced data modeling, analysis, and governance to drive operational and clinical improvements.

Lead GTM analytics for Sales Operations: build and maintain dashboards, run SQL analyses on pipeline/booking/territory/productivity, improve Salesforce data quality, document metrics, support forecasting and ad-hoc GTM analysis, and leverage AI tools to automate and accelerate insights for GTM leadership.

Lead AMS360 data conversion projects: analyze source data, develop field-level mappings, execute and validate test conversions, reconcile data quality issues, use agentic AI to accelerate mapping/validation, maintain documentation, and support go-live activities under aggressive timelines.

Design and build a modern data foundation: develop and scale ETL/ELT pipelines, dbt models and macros, semantic/metric layers, and analytical apps. Ensure pipeline reliability and observability, document systems, gather stakeholder requirements, and contribute to cross-functional analytics and ML initiatives.

Lead data-driven initiatives to analyze complex datasets, build dashboards, present insights to leadership, and drive continuous improvement projects to improve operational performance and inform strategic decisions.

Build and operate Databricks-based lakehouse pipelines (medallion/Data Vault 2.0), resolve identity across systems, enable near-real-time CDC, integrate external partners, add observability, and partner with AI/product teams to deliver trustworthy data for BI, ML, and in-product features.