Top Data & Analytics Jobs in Portland, OR

Lead architecture and delivery of master data management solutions, drive large projects, improve data quality and operations, design taxonomies, and mentor teams to achieve operational excellence and client satisfaction.

Develop scalable business intelligence, automation, advanced analytics, and data products using integrated data sources. Build reusable data assets, pipelines, dashboards, and reporting solutions with SQL, Power BI, Python, Snowflake, and Databricks. Identify trends, exceptions, root causes, and credit risk insights while partnering with business, technology, risk, and executive stakeholders. Apply software development practices, version control, testing, agile delivery, and responsible AI tools to modernize reporting and improve operational decisions.

Provides GIS mapping, spatial analysis, cartographic production, web maps, dashboards, and geospatial data management for environmental and multidisciplinary projects. Supports field data collection, quality assurance, data conversion, technical troubleshooting, project deliverables, and collaboration across offices. Uses Esri ArcGIS platforms to analyze and present spatial information, mentor colleagues, and deliver client-focused geospatial solutions.

Designs and builds modern data applications, pipelines, transformations, enrichment processes, provisioning layers, and interfaces supporting clinical and operational healthcare processes. Analyzes clinical data to identify trends, collaborates with Product, Platform, and Architecture teams, mentors junior data engineers, and evaluates emerging technologies. The role emphasizes cloud computing, big data, data science, modern development frameworks, source control, documentation, and repeatable engineering practices.

Collects and enters investment manager, index, custodian bank, and client data for the Performance Measurement and Analytics Department. Reconciles data with third parties, troubleshoots discrepancies, maintains deadlines and procedures, downloads financial information using industry databases, and supports team members. The role requires strong attention to detail, communication, organization, analytical and problem-solving skills, proficiency with Microsoft Office, and the ability to work independently in a deadline-driven environment.

Manages fisheries data requests, develops SQL retrieval and validation scripts, documents business rules and data definitions, produces statistical reports, defines database requirements, creates reusable database objects, and administers user accounts and access policies. The role also coordinates with agencies, researchers, and other stakeholders to resolve data issues and ensure accurate, standardized, timely information for fisheries management and research.

Designs, develops, tests, and maintains reports, analytical models, programs, and documentation supporting health plan operations. Uses SQL, ETL, reporting, and database technologies to translate business requirements into data-driven solutions. Manages analytical workspaces, resolves cross-departmental issues, participates in peer reviews, and mentors team members and business partners.

Supports Finance data governance initiatives by defining standards, documenting requirements, analyzing data quality, managing data-related issues, and coordinating Finance, Data, and Technology stakeholders to improve consistency, transparency, controls, and decision-making.

Leads Columbia’s North America Commercial Analytics function, unifying reporting, metrics, data sources, and decision-making across wholesale, DTC, marketing, merchandising, and consumer insights. Builds analytics capabilities, operating rhythms, and high-performing teams while translating commercial, consumer, market, and financial data into growth and profitability recommendations. Partners with technology teams on analytics platforms and champions AI-enabled decision support. Advises executive leadership through strategic analysis and fact-based insights.

Designs, builds, and maintains data pipelines, processing systems, APIs, ETL processes, and data integration infrastructure. Implements data quality and governance practices, supports data scientists and analysts, and works with data warehouses, data lakes, cloud technologies, and large datasets. The role also requires ongoing learning about data technologies and occasional driving.