Top Senior Analysis Reporting Jobs in Spokane, WA

The Senior Data Architect designs and implements data architecture solutions, leveraging modern platforms and methodologies to enhance data management, modeling, and integration across applications and stakeholders.

As a Principal Statistical Programmer, you will manage statistical programming tasks in clinical trials, ensuring high-quality data reporting and compliance with regulations.

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

As a Senior Data Analyst, you'll provide actionable insights by analyzing product and engineering data, partnering with leadership on metrics frameworks and decision support for product delivery.

The Staff Analytics Engineer will establish a data foundation aiding various teams at Kit by refining reporting models, ensuring consistent metric definitions, and enhancing stakeholder self-service capabilities.

The Senior Data Analyst will support marketing and sales, drive growth through analytics, and collaborate with key stakeholders to enhance data-informed decision making.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

The Director of Analytics will lead the analytics strategy and operations for a top-grossing mobile app, driving data-driven decision-making and insights.

Lead analytics engineering: architect, build, and maintain scalable data pipelines and dbt models; ensure data is research-ready; partner with Engineering, Data Science, and Commercial teams; implement product analytics and optimize data workflows for scale.