Top Data & Analytics Jobs in Seattle, WA

Leads analytics for Chewy’s Voice of Customer organization by integrating customer, operational, survey, sentiment, and behavioral data. Builds dashboards, measurement frameworks, alerts, governance standards, and self-service analytics. Identifies customer friction, risks, root causes, and business impacts; conducts forecasting, experimentation, segmentation, and regression analyses. Develops executive-ready recommendations, partners with senior stakeholders, monitors customer-impacting events, and coaches analysts and cross-functional teams.

Own measurement strategy and instrumentation quality for web and mobile initiatives. Translate business goals into tagging specifications, KPIs, event schemas, and acceptance criteria; partner with marketing, product, engineering, and analytics teams; validate releases; troubleshoot tracking issues; govern data standards; and ensure behavioral data produces reliable, analytically accessible datasets and reporting.

Executes compensation processes, validates payments and performance data, investigates compensation issues, and develops reports and decision-support tools. Analyzes trends, risks, and plan effectiveness while translating findings into recommendations for leadership. Collaborates on compensation initiatives, supports senior stakeholders, and provides backup and cross-training to maintain operational continuity.

Own cross-functional data-platform and infrastructure initiatives from discovery through production operation. Build reliable queries, pipelines, models, APIs, integrations, and reporting systems for secure, auditable regulatory data sharing. Translate legal and operational requirements into technical specifications and delivery plans, develop AI-enabled workflows with governance and human oversight, lead testing and release readiness, establish reusable automation patterns, and mentor junior engineers while collaborating with global stakeholders.

Own analytics engineering for the machine infrastructure supply chain team. Build and maintain semantic layers, trusted data models, metrics, dashboards, and analytics-ready datasets using dbt and modern data platforms. Analyze inventory trends, optimize stock levels, investigate discrepancies, and develop supply chain KPIs. Partner with data engineering, finance, product, operations, planners, and buyers while improving inventory planning, replenishment, ERP processes, and warehouse efficiency.

Designs and maintains SQL/Python data pipelines, warehouse models, and Power BI dashboards supporting finance planning, forecasting, budgeting, and book close. Owns solution architecture from requirements through deployment, validates data and systems, resolves process and reliability gaps, and manages multiple enhancements. Collaborates with business and technical stakeholders, mentors analysts, leads continuous improvement, documents solutions, trains users, and develops automated and AI-enabled efficiencies.

Build and own scalable finance and revenue data pipelines, models, and datasets supporting ARR, NRR, bookings, billing, and revenue attribution. Ensure data quality, reliability, monitoring, reconciliation, and self-service access while partnering with Finance, Revenue Operations, Analytics, Product, and Engineering.

Leads the strategy, architecture, and deployment of AI-enabled business intelligence infrastructure. Designs governed semantic layers, data models, and BI systems using dbt and enterprise data warehouses. Manages and coaches a technical engineering team, partners with executives and cross-functional stakeholders, and ensures reliable, high-performing data pipelines, warehouses, and reporting tools. The role also advances AI-driven analytics, data discovery, and self-service reporting across the organization.

Leads business intelligence and analytics engineering initiatives for Snap’s People Team. Designs scalable data pipelines, models, data products, dashboards, and self-service analytics solutions. Translates business needs into technical requirements, conducts statistical analysis, improves data quality and operational reliability, and delivers actionable insights. Owns systems end to end while mentoring team members and communicating effectively with executives, business partners, analysts, and technical teams.

Lead end-to-end quantitative market research, including research planning, surveys, advanced statistical analysis, synthesis, and stakeholder presentations. Build and manage brand and sentiment measurement programs, identify customer and market trends, and provide strategic recommendations for growth and product opportunities. Partner with business leaders, promote research-driven decision-making, and mentor junior researchers while scaling the organization’s research practice.