Top Senior Analytics Jobs in Portland, OR

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.

Lead analytics for Wealth Solutions: analyze client segmentation, revenue, and operational data; build models for capacity and workforce planning; produce insights and recommendations for senior leadership; partner with BI and Finance to improve advisor productivity, client experience, retention, and revenue growth; support strategic projects and translate complex data into clear presentations.

Manages Finance analytics engineering and automation, building governed Snowflake and SQL data products, consumption layers, reconciliations, controls, workflows, and integrations. Partners with FP&A, Data Engineering, and business teams to translate Finance requirements into reliable technical solutions. Leads lineage analysis, testing, monitoring, documentation, AI-assisted workflows, production support, and team development while maintaining clear ownership between Finance and enterprise data teams.

Build and maintain dbt and semantic data models in Snowflake, develop ingestion and transformation pipelines, define trusted product metrics, and improve data collection. Partner with Product and Engineering to support experimentation and feature analysis. Establish data quality testing, documentation, HIPAA-aware access controls, and compliance practices. Use and validate AI-generated code and Snowflake Cortex outputs while raising technical standards across the team.

Build customer health scores, churn and expansion analytics, retention dashboards, automated alerts, and executive reports. Maintain integrations among databases, CRM, and BI tools while improving data quality and standardizing reporting. Lead AI adoption for analytics, validate generated insights, and enable customer-facing teams to make informed retention and expansion decisions. Requires strong BI, logistics or supply chain analytics, dashboarding, data integration, communication, and customer-focused skills.

Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.

Develop customer analytics that improve retention, growth, adoption, and operational performance. Build and maintain BI dashboards, customer health metrics, churn-risk reporting, and predictive models. Partner with Client Success, Product, Sales, and Operations to translate complex findings into actionable recommendations. The role also owns data quality, governance, reporting automation, workflow improvements, and stakeholder communication.

Develop and modernize Tableau dashboards for People Analytics, improving visualization, usability, performance, and self-service insights. Design and maintain Tableau row-level security for sensitive employee data, including dynamic access controls and entitlement mappings. Build optimized data sources and models using Snowflake and SQL, troubleshoot data and integration issues, document solutions, and collaborate with technical and business stakeholders on scalable analytics products.

Own the analytics engineering roadmap, architecture, and production data models. Build and optimize dbt models using SQL, Python, and Databricks; establish dimensional models, governed metrics, testing, documentation, lineage, monitoring, and CI/CD practices. Partner with data engineering, analysts, BI developers, and stakeholders to deliver reliable analytics products, improve performance and cost efficiency, investigate data quality issues, and mentor team members.

Build and maintain reusable analytical data products, canonical entities, data marts, semantic layers, and governed metrics across business domains. Establish modeling, documentation, quality, lineage, and change-management standards; improve data reliability, self-service analytics, and production governance. Partner with Data Platform, Trust, Data Science, Applied AI, and business stakeholders on orchestration, observability, access controls, feature tables, model outputs, and shared metric definitions. Remain hands-on with SQL, Python, testing, code reviews, documentation, and technical coaching.

Lead GTM analytics across performance measurement, channel economics, data governance, forecasting, planning, and executive reporting. Own metric definitions, data standards, analytical priorities, and business requirements while partnering with Marketing, Data Science, Finance, RevOps, and Engineering. Analyze funnel, attribution, CAC, payback, conversion, retention, pipeline, and territory performance, translating findings into investment recommendations and strategic decisions for senior leadership.

Contract Analytics Engineer maintaining Looker and LookML dashboards, reporting, data operations, sales pacing, data QA, vendor workflows, board reporting, forecasting, and planning support during a director’s maternity leave. The role requires strong SQL and Snowflake skills, analytics engineering experience, vendor management, Git/GitHub proficiency, documentation, and independent work in a lean data team.

Supports provider business development through bundled-payment pricing analytics, financial modeling, and strategic analysis. Builds and refines analytical tools and datasets, develops models for new healthcare bundles, supports provider negotiations, and partners with data science and engineering teams on optimization and data infrastructure. Requires healthcare knowledge, quantitative skills, cross-functional collaboration, and the ability to manage multiple priorities in a fast-paced remote startup environment.

Designs, builds, secures, monitors, and supports scalable data platforms across public and multi-cloud environments. Develops batch and streaming pipelines, ELT processes, data lakes, warehouses, APIs, and integrations with transactional systems. Works with SQL and NoSQL databases and technologies including Spark, Hadoop, Databricks, Snowflake, Kinesis, and Lambda. Leads projects, presents to leadership, collaborates with clients and Scrum teams, troubleshoots issues, and enables analytics and machine learning initiatives.

Provides hands-on technical leadership for data analytics support across enterprise customers. Responsibilities include resolving complex SQL, cloud platform, ELT, data pipeline, data warehouse, and BI issues; optimizing analytics solutions; conducting root cause analysis; reviewing SQL and BI changes; mentoring analysts; automating support processes; and advising customers on Tableau, Power BI, and modern analytics architecture.

Build and own commercial data models in Snowflake and dbt for ARR, bookings, pipeline, account scoring, ICP fit, upsell, and whitespace analysis. Establish semantic layers, governance, documentation, testing, monitoring, and CI/CD practices. Partner with Sales, Marketing, Finance, and enterprise data teams to deliver trusted self-service analytics, improve data infrastructure, and develop AI-powered automation. This senior individual contributor will own the roadmap and mentor analysts on data modeling and dbt.

Analyze healthcare, financial, and utilization data to identify inefficiencies, support data-driven decisions, maintain dashboards, build analytical models, communicate insights, and monitor improvement initiatives across the organization.

Own client relationships and analytics strategy across digital measurement and GEO initiatives. Architect, audit, and QA GA4 and Adobe Analytics implementations; develop measurement frameworks, dashboards, experimentation plans, and causal analyses. Present insights to executive stakeholders, manage analytics workstreams, mentor teammates, and build AI-assisted workflows, automations, and scalable systems. The role combines traditional analytics with measurement of AI-powered search visibility and customer behavior.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

Build and maintain scalable ELT pipelines, dbt models, semantic layers, and governed product analytics assets. Partner with Data Engineering, Product Engineering, Data Governance, analysts, and product managers to define trusted metrics, monitor data quality, document taxonomies, and support self-service analytics. Translate product usage telemetry into certified metrics for expansion and upsell analysis, while communicating technical concepts to technical and non-technical stakeholders and driving engineering best practices.

Own Hercules’ full data stack, including ETL from third-party providers into BigQuery, data modeling with dbt and medallion architecture, semantic-layer metric definition, and self-service business intelligence in Omni. Build reliable, maintainable systems and dashboards while applying strong software architecture, API design, code quality, and AI-assisted development practices.

Own marketing channel performance tracking, reporting, experimentation, dashboards, forecasting, and LTV analysis. Develop measurement frameworks, identify data issues, and translate complex findings into actionable recommendations for Marketing, Growth, Product, and Finance stakeholders. The role requires strong SQL, BI dashboarding, marketing measurement, experimentation knowledge, and effective analytical communication, with AI tools used to accelerate reporting and analysis.

Designs and maintains healthcare analytics infrastructure, production data models, semantic layers, and transformation pipelines using advanced SQL and analytics engineering practices. Integrates payer claims, EMR, clinical, attribution, quality, and operational data. Performs ad hoc analysis, defines standardized healthcare metrics, validates data quality, optimizes queries, documents data flows, and partners with clinical, operational, IT, and payer stakeholders to support value-based care and enterprise reporting.

Designs scalable data models, optimized SQL queries, analytics infrastructure, semantic layers, and data applications. Partners with data science, product, engineering, and business teams to enable dashboards, self-service analytics, reporting, and enterprise data-driven decision-making. The role also establishes analytics engineering best practices, improves developer experience, and supports secure, compliant data warehousing.