Top Data & Analytics Jobs in Seattle, WA

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Implement and monitor pricing strategies across consumer lending: translate strategy into technical specs, maintain audit trails, collaborate with engineering, validate data pipelines, build automated controls and Tableau dashboards, support risk management, and coordinate execution with internal and external partners.

Design and administer enterprise dashboards and reporting solutions (Tableau, Power BI, Microsoft Fabric). Translate complex business questions into compelling data stories, partner with stakeholders and BI engineers, champion visualization standards and governance, mentor analysts, and improve reporting usability and trust across the organization.

Design and execute advanced statistical and data analyses for client projects, using tools such as R, Tableau, SAS, VBA, and Excel. Translate data into actionable insights, communicate findings to clients and internal teams, collaborate on solution implementation, and take ownership of project deliverables.

Lead strategy, governance, and delivery of trusted digital interaction and behavioral data across web and mobile. Define metadata, taxonomy, measurement, quality, lineage, access, and controls to enable reporting, experimentation, personalization, AI/ML, and marketing activation while coaching teams and partnering with cross-functional stakeholders.

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

Lead enterprise-scale Akeneo PIM implementations, including solution architecture, platform configuration, data architecture, API development, and third-party integrations. Collaborate with developers, architects, clients, and stakeholders to deliver digital transformation projects. Ensure data privacy, security, and lifecycle protection while documenting technical solutions, gathering requirements, managing expectations, and mentoring junior team members.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Architects, deploys, and operates scalable data platform infrastructure supporting analytics. Responsibilities include administering Airflow and Superset, managing Terraform infrastructure, building CI/CD pipelines, enforcing security and compliance, developing DBT data models, cataloging assets in OpenMetadata, writing Python automation, and mentoring engineers. The role requires extensive infrastructure and data engineering experience across cloud platforms, containers, data security, and workflow orchestration.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.