Top Senior Analysis Reporting Jobs in Portland, OR

Lead a team to analyze sales data, build and maintain Power BI and Excel reporting, leverage AI and automation for pipeline and lead scoring, align cross-functional GTM strategies, ensure data quality, and deliver actionable, executive-ready insights to drive sales performance and quota attainment.

The Data Analyst will support operational reporting and stakeholder needs, working with SQL and Artiva to meet business requirements through data and reporting solutions.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.

The Senior Azure Data Consultant will build and maintain data pipelines, develop lakehouse solutions, optimize ETL processes, and support analytics capabilities in a Microsoft Fabric environment.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

Own Mixpanel and partner closely with Product to turn product-level data into decision-grade insights. Define instrumentation and event taxonomy, build dashboards and notebooks, run cohort and retention analyses, design and analyze A/B tests, and collaborate with data engineers to model product event data. Document metrics, maintain a living glossary, and translate findings into actionable product recommendations.

Own end-to-end analytics modeling for a business domain: build and maintain dbt models and business marts on Snowflake, develop the BI semantic layer, define consistent metrics, create self-serve data products, and partner with Finance, Sales, Marketing, CS, and RevOps. Validate upstream data with the Data Platform team and translate ambiguous business questions into production-ready data models.

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.