Top Analysis Reporting Jobs in Portland, OR

Designs, administers, and optimizes data systems supporting FSA IAM applications. Develops migration plans from legacy AIMS and PAS systems, creates data models, mappings, layouts, dictionaries, and integration processes, and supports analytics and fraud detection. Manages database configuration, performance tuning, monitoring, backups, capacity, secure data handling, encryption, network data flows, token management, and documentation while collaborating with development, security, and operations teams.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.

Lead WEX’s semantic data platform and Data-as-a-Service strategy. Define architecture and roadmap, build trusted semantic business objects and governance capabilities, enable AI and agentic applications, and drive enterprise adoption. Lead engineers, architects, and technical leaders while partnering with Product, AI, Analytics, Risk, Finance, and business teams. Translate complex business concepts into scalable platform abstractions and oversee modernization of large-scale data ecosystems.

Conduct individual and institutional prospect research, donor profiling, pipeline qualification, due diligence, and risk assessments. Synthesize financial, philanthropic, and relationship information into briefings, event snapshots, leadership summaries, and board bios. Proactively identify new donor prospects, monitor wealth and philanthropic trends, and support board and geographic expansion initiatives. Train Development staff on research tools, establish service protocols, and manage research requests independently while protecting confidential information.

Lead Salesforce data migration and quality activities for a Department of Veterans Affairs modernization program. Analyze SQL Server data, create source-to-target mappings, execute ETL and Salesforce loading, validate and reconcile records, implement data quality controls, and develop migration and application test plans. Track defects, support automated monitoring and testing, collaborate with architects, developers, stakeholders, and provide migration status, risk, and quality updates.

Own GTM reporting and analytics across Salesforce, warehouse systems, Tableau, and Excel. Build trusted dashboards, define metrics, investigate data quality issues, and lead analysis for pipeline, forecasting, territory design, capacity planning, productivity, and resource allocation. Partner with GTM, CRM, Data, and Systems stakeholders to improve reporting architecture and support leadership decisions. Use AI tools to automate analysis and develop internal analytics workflows.

Own end-to-end analytics for the Pro product: build production data pipelines and dbt models, define north-star metrics, design dashboards and full-funnel reporting, lead A/B experimentation and causal inference, embed AI tooling, and deliver clear data-driven recommendations to product and leadership.

Build and own the data platform backbone: design ingestion patterns, Snowflake warehouses, governance, and freshness strategy. Implement reliable batch and streaming pipelines, data quality, observability, and onboarding processes. Lead legacy migrations, create data contracts and SLAs, and apply AI-native tooling to automate debugging, documentation, and operational workflows while partnering with Analytics, Engineering, and vendors.

Own the companys end-to-end data graph, ensure data quality and lineage, and deliver Sigma dashboards and client-facing reports. Act as single owner for triage, prioritization, and translation of business questions into actionable insights, partnering closely with data engineering and business leaders to set standards for production-ready reporting.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.