Top Senior Analysis Reporting Jobs in Portland, OR

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

Collect and analyze competitive intelligence and conduct due diligence and investigations on investment candidates and related entities. Design data collection methods, use research, network analysis and AI/automation tools to produce high-quality reports and actionable recommendations for senior stakeholders, and improve workflow productivity.

Design, build, and maintain scalable ETL/ELT pipelines and product-level data architectures. Improve pipeline performance and data freshness, lead code/design reviews, mentor engineers, and collaborate with Data Science, Product, and Engineering to make data reliable and accessible.

Lead end-to-end data conversion projects: analyze and profile legacy data, develop mappings and ETL/ELT transformations, validate and load data, resolve quality issues, coordinate cutovers, mentor juniors, and leverage generative AI to accelerate delivery.

Perform cross-product credit analytics to inform underwriting, limits, and portfolio strategy. Build customer credit profiles, run experiments (A/B tests), uncover insights, recommend and execute policy changes, and communicate results to leadership. Leverage internal and external data, predictive techniques, and AI tools to optimize approvals, risk, and product performance while balancing growth and loss.

Lead design and buildout of an Operations Intelligence Warehouse (BigQuery, dbt, Metabase), define metrics and data quality standards, create dashboards for throughput and cycle time, join ops to GTM/financial data, run variance/root-cause analyses, and partner with Data Engineering and stakeholders to turn operational telemetry into actionable insights.

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

Architect and implement scalable Azure Lakehouse solutions (Databricks, Microsoft Fabric). Lead cloud data migrations, build ETL/ELT and streaming pipelines, enforce data governance and security, advise clients, run workshops, and mentor teams while managing multiple engagements.

Responsible for compiling, cleaning, enriching, analyzing, and visualizing sales and pipeline data across systems. Build forecasting models, dashboards, and reports; present insights to stakeholders and collaborate cross-functionally to improve processes and reporting.

Architect and deploy scalable Inventa data-management solutions, lead complex enterprise integrations (APIs, on-prem, cloud, SaaS, data lakes), resolve architectural performance and access issues, create global architecture guides and documentation, and feed product improvements through field insights. Customer-facing, cross-functional collaboration with Sales, Customer Success, and Product.