Top Data & Analytics Jobs in Seattle, WA

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.

Leads business analysis and contact interaction analytics to deliver insights, dashboards, reporting solutions, modeling, and data-driven recommendations. Partners with marketing, product, platform, and cross-functional teams to define success metrics, optimize customer experiences, prioritize resources, and support strategic and operational decisions. Administers standardized reporting structures and self-service analytics environments while communicating complex findings to leaders across the organization.

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.

Build, maintain, and optimize complex batch and streaming data pipelines across structured and unstructured sources. Partner with Engineering and Analytics teams to develop data exchange systems, translate business needs into technical solutions, ensure data and code quality, automate processes, support development environments, and participate in weekly on-call rotations.

Lead development of scalable econometric and causal-inference methods (DiD, RDD, IV, synthetic controls, panel data) to measure long-term marketplace impact. Integrate causal insights into production ML systems, influence product strategy, present findings to executives, and mentor data scientists and economists.

Researches air cargo industry trends, airline and logistics variables, and future freighter demand. Develops statistical models, market forecasts, and scenario analyses; provides insights into airline cargo strategies; creates presentations and white papers; and supports technical sales on air cargo and freighter issues. The role communicates complex findings to global leadership and external audiences and contributes to Boeing’s long-term air cargo market outlook.