Top Analysis Reporting Jobs in Boise, ID

Audit and reconcile marketing and lead data end-to-end, maintain campaign tracking and platform integrations, troubleshoot data flow issues, manipulate large datasets to identify discrepancies, coordinate with vendors and stakeholders, and recommend process improvements to ensure accurate marketing-to-intake reporting.

Design and own a federated, multi-institution medallion lakehouse on Azure Databricks and Microsoft Fabric. Define federated multi-tenant architecture, Unity Catalog security, data ingestion from ERP/SIS/LMS/CRM/Workday, and platform standards. Provide hands-on architecture guidance, review designs, document decisions, and partner with governance, delivery, and engineering teams to enable production analytics at multiple institutions.

Design and build Snowflake transformation layer and migrate legacy SQL to versioned dbt models. Define conformed dimensions/facts using Kimball principles, set modeling and CI/CD standards, implement data quality/lineage, support BI migration and AI/ML readiness, and mentor future hires. Hands-on work in dbt, SQL, and Python with stakeholder collaboration and governance for financial and operational data.

Design, build, and maintain data warehouse infrastructure, semantic/dimensional models, metrics layer, and BI dashboards (Sigma, Power BI, Databricks). Build secure ELT pipelines, enforce governance and row-level security (Entra ID), enable self-service analytics and AI/ML integrations, triage BI issues, train stakeholders, and collaborate in Agile to deliver reliable, performant reporting and curated data products.

Build and maintain CS reporting, dashboards, and health score models to identify renewal risk and inform strategy. Deliver executive reporting, collaborate cross-functionally to improve data quality, and develop predictive analytics and longitudinal tracking to reduce churn.

Develop and maintain automated ETL solutions using SSIS, Oracle SQL, and PL/SQL to move data between Oracle and SQL Server systems. Design database, data warehouse, and ETL interfaces; analyze requirements; establish development, documentation, and testing standards; manage change deployments; and monitor project schedules. Collaborate with stakeholders, assess database changes and downstream impacts, document solutions, communicate issues, and mentor junior staff.

Designs and builds scalable, reliable, observable batch and streaming data pipelines and models. Partners with stakeholders on data integration, validates data quality, writes tests, participates in code reviews, documents solutions, troubleshoots production issues, and aligns technical work with business needs. The role requires strong programming, database, data modeling, governance, and Databricks knowledge, with preferred experience in Spark, AWS data services, CI/CD, testing, orchestration, and transformation frameworks.

The job description provides no substantive responsibilities or qualifications beyond the Director, Data Engineering title. The posting contains general company information, benefits, equal employment opportunity language, and application details. Specific duties, required technologies, experience, education, and other role expectations are marked as TBD or not provided.

Design, build, deploy, and maintain configurable, metadata-driven analytics platforms and workflow/decision engines for Risk Adjustment. Partner with analysts to translate processes into auditable, scalable solutions; own full lifecycle, production support, monitoring, and performance optimization while applying AI where beneficial.

Lead Databricks-based enterprise data and analytics modernization programs. Define future-state architecture, drive platform modernization, ensure security, scalability, cost optimization, and mentor teams while delivering AI-ready data platforms and governance.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.