Top Analysis Reporting Jobs in Boise, ID

Analyze market and live data to set dynamic ticket prices using Uptick, build strategic pricing recommendations, communicate with clients about strategy and performance, and collaborate with BI and engineering to improve product performance.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

Analyze digital marketing campaigns and leverage data to inform business decisions, drive optimizations, and improve performance metrics.

Design, build, and maintain scalable ELT data pipelines and models to power reporting, analytics, and operational workflows. Troubleshoot data quality and performance, participate in incident response, support CI/CD deployments, collaborate with cross-functional teams, and contribute to data platform modernization and engineering best practices.

Lead architecture and implementation of cloud-native data platforms on Google Cloud (BigQuery). Build unified batch/streaming pipelines, enforce IaC with Terraform, implement open table formats and governance (Dataplex/Data Catalog), automate data quality/lineage, partner with analytics and product teams, and mentor data engineers.

Lead the vision and execution of a scalable, multi-tenant data platform: own ingestion, warehouse, transformation, BI, and AI-on-data layers. Manage and grow a data engineering team, define engineering standards (CI/CD, infra-as-code, testing, lineage), productize integrations, and collaborate with Product, Engineering, and GTM for client onboarding and data delivery.

The Data Architect will design scalable data solutions, enforce data standards, lead architecture discussions, and collaborate with stakeholders. Responsibilities include managing platforms, ensuring data compliance, optimizing pipelines, and guiding teams toward data-driven solutions.

Build reliable data models and semantic layer for AI-powered analyses. Support Product, Finance, and Customer Success with SQL-based analytics, BI dashboards, and stakeholder storytelling. Standardize data team processes, prioritize work, and collaborate across company to enable data-informed decisions.

Design and advance enterprise data and BI architecture: optimize OLTP/OLAP models, establish modeling/integration/governance standards, lead POCs, mentor teams, enable AI/ML, and guide cross-functional implementation from concept to production.