Top Senior Analysis Reporting Jobs in Boise, ID

Maintain and integrate investment data; build data systems and ETL pipelines; analyze large datasets; produce visualizations and reports (Tableau/Power BI/D3.js); improve data quality and governance; develop analytical tools; collaborate with clients, system architects, and product teams.

The role involves developing models for product flow and capacity forecasting, utilizing mathematical techniques, data analysis, and programming languages, while collaborating with engineers and business users.

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.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

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.

Lead design and execution of an enterprise data governance framework: set policies for data quality, metadata, lineage and privacy; run governance councils; operationalize data ownership and stewardship; implement data cataloging; embed controls in pipelines; ensure compliance and drive organization-wide adoption and change management.