Top Data & Analytics Jobs in Seattle, WA

Designs and maintains scalable data pipelines and infrastructure, establishes data governance and quality standards, and drives technical decisions across Headway’s data platform. Partners with Product, Engineering, Analytics, Data Science, Infrastructure, Finance, and Insurance Systems to improve architecture, performance, reliability, security, and AI-readiness. Ensures data is complete, traceable, trustworthy, and suitable for powering internal tools and AI-driven insights.

Analyze customer support experiences and define success metrics at Remitly. Partner with product, program, engineering, and analytics teams to deliver insights influencing product and process design. Communicate metrics and recommendations to stakeholders, manage strategic analytics initiatives, build dashboards, model complex scenarios, conduct experimentation, and drive measurable business outcomes.

Data Engineering Interns will define metrics, instrument logging, ingest and model data, transform datasets, ensure data quality and governance, and support visualization, reporting, alerting, and scalable systems. They will partner with product, analytics, and data consumers to improve product engagement, efficiency, costs, and strategic decision-making. The 12-week, full-time internship includes technical training, mentorship, and hands-on project experience.

Leads a team of 7–8 analytics professionals supporting user growth, activation, engagement, retention, conversion, and rentals analytics. Owns experimentation strategy, A/B and multivariate testing, KPI frameworks, funnel diagnostics, dashboards, Snowflake data models, and Tableau self-service analytics. Partners with Product, Engineering, Design, and Finance to guide growth investments and senior-level decisions. The role also requires hiring, coaching, AI-enabled analytics workflows, and strong statistical and causal reasoning.

Leads the People data ecosystem, including Snowflake workforce data models, pipelines, governance, metric certification, and data quality. Develops scalable workforce analytics products using Visier and Snowflake, enables governed AI-driven insights, replaces manual reporting with self-service solutions, and manages a high-performing team of data and analytics professionals.

Design and maintain scalable data models, batch and streaming ETL pipelines, and end-to-end data workflows supporting business intelligence, machine learning, and operations. Ensure data quality, consistency, governance, traceability, and reliable delivery across distributed systems. Partner with business teams, platform engineers, and product managers to translate requirements into documented solutions and resolve data issues. The role is based in Seattle with three days per week in the office.

Analyze product and healthcare billing data to support product decisions, reporting, experimentation, and claims collection improvements. Build and maintain dashboards, develop scalable datasets, conduct A/B testing, create data visualizations, and communicate actionable insights. Collaborate with product stakeholders, data scientists, and engineers on data modeling, OKRs, data quality, and pipeline reliability for Billing and Payments features.

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.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.