Top Analysis Reporting Jobs in Boise, ID

The Lead Data Migration Specialist enhances system automation and accuracy, handling data collection, analysis, and onboarding. They resolve discrepancies, implement optimizations, and collaborate with development teams, ensuring efficient data management and continuous service improvement.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Support Digital Workplace initiatives by gathering and documenting requirements, analyzing operational data and service metrics, identifying improvement opportunities, supporting testing and UAT, assisting change management and adoption, and producing reports and dashboards to drive automation and operational improvements.

Support stakeholders to gather and document requirements for analytics, reporting, data products, and AI solutions. Perform exploratory data analysis with SQL, identify data quality issues, create user stories and technical specifications, coordinate with engineering and BI teams, facilitate discovery workshops, and support UAT and standardized analytics practices.

Monitor and verify accuracy of live e-sports game data feeds in real time, identify and resolve discrepancies, cross-check multiple sources, escalate issues, and collaborate to streamline processes. Maintain knowledge of schedules, rosters, rule changes, and key metrics to ensure contextual data accuracy throughout the season.

Lead design and execution of Toast's enterprise data governance: define strategy, build governance frameworks, policies, business glossary, Data Governance Council, ensure compliance (GDPR/CCPA/SOC2/PCI-DSS), run maturity assessments, enable data literacy, and grow the governance team to drive adoption across domains.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead design and governance of enterprise-scale data architecture (warehouses, lakehouses, streaming). Define standards for data quality, lineage, observability, and AI-enabled workflows. Mentor engineers, serve as technical escalation, and translate business needs into long-term data architecture and governance strategies.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.