Top Hybrid Data & Analytics Jobs in Seattle, WA

The Associate Data Solutions Architect designs and maintains data pipelines, collaborates with analysts, develops ETL processes, and ensures data quality for analytics in supply chain.

The Senior Data Solutions Architect will develop analytics solutions, manage data pipelines, and ensure data quality and compliance in the Finance sector.

The Process Analyst manages supply chain data governance, ensuring quality control, policy enforcement, and data usability across various supply chain functions.

The Lead Data Analyst will estimate marketing incrementality and improve performance using media mix modeling and predictive modeling. Responsibilities include mentoring other analysts, partnering with teams, and developing predictive models to drive business outcomes.

The Category Analyst will manage category performance through vendor engagement, data analysis, and collaboration across teams while supporting category goals.

Lead data-driven strategies and analytics at PwC, motivating teams to improve business performance and decision-making through advanced techniques and collaboration.

The role leads Clinical Data & Information Sciences in drug development, ensuring data integrity, compliance, and continuous improvement while collaborating with cross-functional teams to enhance business processes and experience.

Lead architecture and delivery of SoFi's data platform: build scalable data pipelines, drive cloud-native and AI-enabled tooling, enforce governance and security, mentor senior engineers, and support production on-call.

As a Senior+ Agentic Analytics Engineer, you will design and deploy AI systems that provide actionable insights, build analytics tools, and manage the analytics-to-action pipeline to drive business decision-making using AI.

The Decision Analytics Associate will develop statistical models, leverage data analytics, design custom analyses, and communicate findings to clients while advancing their problem-solving capabilities.

The Senior Data Engineer will design and optimize large-scale batch and streaming data pipelines using Scala and Spark, oversee the data engineering lifecycle, and engage in technical discussions to improve system efficiency.

The Head of Data Science - Fraud Insights will lead research on fraud analytics, design predictive studies, manage a team, and communicate findings to influence strategy and policy.