Top Data & Analytics Jobs in Boise, ID

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

As a Data Engineer II, you will build, scale, and optimize data platforms, focusing on ETL/ELT pipelines, and collaborate with data scientists and AI engineers to support data-driven applications and insights.

Manage shopper insights and category growth strategies for Albertsons, leveraging market data to identify opportunities and enhance decision-making. Collaborate with sales teams to develop actionable recommendations to drive growth and build reporting dashboards.

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

Design, develop, integrate, test, and optimize scalable data integration solutions and pipelines for the OneGL finance environment. Support production users and month-end close processes, troubleshoot issues, develop test scripts, and document architectures. Collaborate with technical and business stakeholders, perform gap analysis, and support implementation and post-implementation activities.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.

Partner with Customer Success and CS Ops to build post-sales analytics: customer health scoring, renewal and renewal pipeline reporting, billing and support signal analysis, and expansion/upsell dashboards. Own dashboard ecosystem, translate stakeholder requests into scalable reporting, collaborate with Finance and Data Engineering, and leverage AI tools to accelerate analytic workflows and maintain data quality for retention and expansion decision-making.