Top Senior Analysis Reporting Jobs in Boise, ID

Lead analytics engineering by building and optimizing scalable data pipelines, transformations (dbt), and data models on cloud warehouses. Deliver performant, cost-effective pipelines, dashboards, and AI-assisted tooling while collaborating cross-functionally to enable self-serve analytics.

Design, develop, and support SQL Server databases and related ETL/BI solutions (SSIS/SSRS). Implement database source control, CI/CD with TFS/SSDT, tune performance, maintain security, and collaborate with teams in an Agile/Scrum environment.

Lead BI and data for a large real estate account: design and deliver Power BI dashboards, data governance, integrations, SharePoint and automation solutions, build analytics roadmap, translate data into executive insights, drive process improvement, and lead a technical analytics team.

Lead and grow a data engineering team, set technical standards and roadmap, architect scalable GCP data solutions (ingest, transform, warehouse, serving), ensure pipeline reliability and data quality, partner with analytics and client teams, drive best practices (CI/CD, IaC, governance), and evaluate new tooling.

Design, deploy, and govern enterprise-scale data architectures and platforms to support analytics and AI. Define modeling standards, integration pipelines, data quality, lineage, and security. Lead technical direction, mentor engineers, evaluate AI tooling, and support proofs of concept and solution roadmaps that enable generative AI and RAG solutions.

Lead enterprise insurance analytics across underwriting, claims, operations, compliance and finance. Build dashboards and reporting, ensure data integrity with TPAs, support underwriting and captive program performance, coordinate with actuary for IBNR, advance predictive/benchmarking capabilities, and present insights to leadership.

Develop and optimize T-SQL scripts to transform legacy SIS data for loading into the Jenzabar platform, manage multiple conversion projects, communicate with clients and internal teams, adhere to project plans and timelines, estimate custom work, and improve conversion processes.

Lead a team to design, build, and maintain cloud data engineering solutions using Microsoft Fabric and Azure Synapse. Responsibilities include architecture, data pipelines, lakehouse and warehousing implementation, governance, performance optimization, mentoring engineers, cross-functional collaboration, support/on-call, documentation, and ensuring reliability and compliance.

Lead marketing analytics: own reporting frameworks, dashboards, and data quality; monitor KPIs; run A/B tests and experiments; build attribution, forecasting, segmentation, and budget-allocation models; automate workflows and drive continuous measurement improvements.

Lead operational management of the Product Classification organization: hire, train, and scale classification and manual QA teams; set metrics, SLAs, and operating cadence; partner with Engineering and Product to improve LLM-driven classification; build processes, rules, and analytic checks to ensure high accuracy at scale.