Top Remote Analysis Reporting Jobs in Portland, OR

Design, build, and operate production-grade data ingestion pipelines and dbt transformations into a Databricks lakehouse. Establish data quality, monitoring, and observability. Partner with Product and Engineering to enable metrics, dashboards, and longitudinal patient analytics supporting clinical and operational decision-making.

Serve as primary DBA SME bridging on-premises SQL Server to Microsoft Fabric. Design hybrid database architectures, implement cloud-based SQL services, establish Data Operations processes and SLAs, manage data integration, security controls, performance tuning, monitoring, and disaster recovery to support analytics and AI workloads.

Design and advance enterprise data and BI architecture: optimize OLTP/OLAP models, establish modeling/integration/governance standards, lead POCs, mentor teams, enable AI/ML, and guide cross-functional implementation from concept to production.

Lead and execute the company data strategy; design and maintain scalable data models and warehouses; drive ETL implementation; enforce data governance; provide analytics and insights to cross-functional teams; manage budgets, hiring, and team development; monitor performance and adopt emerging data technologies to optimize operations.

Support GiveWell research by quality-checking and updating cost-effectiveness models, conducting desk research, summarizing grantee monitoring and evaluation, writing clear public summaries, and performing ad-hoc high-impact projects and project-management support for research investigations.

Design and maintain company-wide dashboards, define KPI frameworks, implement tracking and data governance, write advanced SQL, partner with product and engineering, build predictive/AI-ready data layers, automate reporting, and present insights to leadership to drive operational and financial improvements.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.