Top Healthtech Data & Analytics Jobs in Seattle, WA

Lead complex BI projects to define KPIs, build internal and client-facing Tableau/Power BI dashboards, enforce documentation and metric consistency, perform data analysis and profiling, create BI strategy and roadmaps, mentor junior analysts, and present insights to cross-functional and executive stakeholders.

Lead a team of data scientists to enhance patient experiences through data insights, predictive modeling, and analytics for healthcare solutions.

Build and maintain scalable cloud-native data platforms and pipelines for analytics. Design system architecture, ingest high-volume bounded and unbounded data, optimize performance and cost, write tests and documentation, collaborate with product and EHR specialists, and adopt AI-assisted development tools to improve delivery and quality.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Own the end-to-end architecture and roadmap for MyFitnessPal’s product data stack. Coordinate data engineering, business intelligence, product analytics, and backend teams; establish data movement and standardization practices; lead tool evaluations and platform migrations; implement governance, PII handling, deletion workflows, access controls, and cost optimization; and document architecture standards across the organization.

Define and lead the company’s data architecture strategy, roadmap, and standards. Drive the transition from batch to real-time data platforms, guide decisions on governance, security, quality, scalability, and reliability, and identify practical AI applications. Partner with executive, product, and engineering leaders, establish design reviews, influence cross-functional decisions, and lead a global team of senior data architects.

Analyze business data using SQL, BigQuery, Tableau, Python, and related tools to identify trends, build dashboards, maintain KPIs, and deliver actionable insights. Translate ambiguous business questions into reporting, automation, AI-powered workflows, and technical solutions. Partner with technical and business stakeholders, improve data quality and storytelling, and explore emerging AI technologies such as agentic workflows and LLM-powered automation.

Lead and grow data engineering and analytics engineering teams while overseeing data platform modernization, BigQuery and Looker migrations, reusable dbt models, self-service capabilities, governance, reliability, and data foundations for AI and ML. Partner with technical and business stakeholders to prioritize roadmaps, manage hiring and performance, improve adoption, and protect sensitive healthcare data.

Processes client-requested data changes, creates data transfer packages, and writes SQL queries against Microsoft SQL databases. Conducts risk assessments, verifies data updates and transfer datasets, creates stored procedures, monitors data across databases, and supports clinical study implementation. Requires strong attention to detail, documentation, communication, prioritization, and occasional after-hours technical support.