Top Senior Data & Analytics Jobs in Boise, ID

As a Senior Analytics Engineer, you will design the financial data backbone, integrating ERP data, building profitability models, and enabling data-driven planning in collaboration with Finance and Operations.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

Serve as a client-facing consultant translating business needs into technical specifications, delivering Liquid Data platform solutions, developing reports/dashboards, supporting implementations, and driving technology adoption while collaborating with internal teams and leveraging cloud, API, and BI integrations.

As an EDWH Solution Architect, you'll strategize and engineer Big Data and cloud solutions, lead data architecture initiatives, mentor team members, and ensure integrations meet client requirements while utilizing various tools and technologies.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

The CAT Pricing Lead will manage catastrophe pricing strategy, integrating risk insights into pricing, and leading a team focused on actuarial analysis and portfolio risk management.

The Agentic AI Lead will design AI-first processes, lead innovation projects, drive cultural change, and partner with leaders to transform operations at Tilt.

Senior individual contributor owning partnerships analytics: lead agent acquisition and product analytics, build risk/commission debt models, define onboarding "aha" metrics, optimize funnels, enable self-serve analytics, integrate generative AI tooling, and mentor junior analysts.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.