Top Analysis Reporting Jobs in Boise, ID

Loads, validates, reconciles, and analyzes client investment data using Excel and SQL. Identifies discrepancies, resolves data issues, and improves repeatable onboarding and migration workflows. Collaborates with development teams to enhance automation, accuracy, and delivery speed. Applies accounting, financial markets, securities, normalization, reporting, and reconciliation knowledge while coordinating complex activities in an agile environment.

Supports marketing measurement and analytics by collecting, validating, and analyzing data from digital platforms, CRM systems, web analytics, surveys, and internal systems. Develops Power BI dashboards, scorecards, executive reports, visualizations, and KPI summaries. Identifies trends, risks, opportunities, and data quality issues, then provides actionable recommendations. Explores AI-enabled analytics and automation to improve reporting efficiency and insight generation.

Maintain and extend Snowflake and dbt marketing data models, dashboards, semantic models, KPI frameworks, and AI-agent validation processes. Investigate data quality issues, document metric definitions, assess downstream impacts of marketing technology changes, and translate stakeholder reporting needs into durable self-service data structures. The role requires collaboration across marketing, sales, IT, and finance to ensure trusted data and accurate AI-generated insights.

Build and operate production data pipelines and dimensional models using Spark, SparkSQL, and cloud lakehouse technologies. Own pipelines from requirements through deployment, monitoring, and iteration; improve data quality, lineage, reliability, and cost efficiency. Partner with data scientists, analysts, product managers, and engineers to support datamarts, KPIs, reporting, and analysis. Participate in business-hours on-call rotations and improve runbooks and alerting.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Own and operate Toast’s enterprise data governance program, including data domain ownership, governance council coordination, policy compliance, business glossary management, metadata standards, catalog adoption, maturity assessments, and data literacy training. The role partners with business stakeholders, data stewards, catalog teams, and leadership to improve data trust, compliance, discoverability, and quality. It requires governance, metadata, SQL, data catalog, program management, and workshop facilitation experience.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Leads the strategy, architecture, implementation, and evolution of enterprise analytics platforms. Responsibilities include designing scalable data platforms, integrating digital and enterprise data, establishing governance and security standards, optimizing analytics and BI capabilities, evaluating cloud technologies, managing platform performance and risks, and mentoring technical teams. The role also requires close collaboration with executives, clients, Product, Engineering, Data Science, Marketing, and business stakeholders.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.