Top Remote Analysis Reporting Jobs in Boise, ID

Manage the full data quality lifecycle for constituent records in Salesforce: deduplication, merges, data appends/enrichment, imports/exports, vendor management, audits, governance, reporting, staff training, and supervise a team focused on CRM data hygiene to support nonprofit fundraising operations.

Support HRIS implementation by extracting, cleansing, validating, and preparing employee data for migration. Reconcile reports, fix duplicates and missing data, create Excel transformation files, maintain data quality, document work, and assist with testing and post-go-live support.

Lead process mining and improvement projects across business areas, develop dashboards and analyses (e.g., Celonis), apply industrial engineering practices, identify root causes, translate functional requirements to technical solutions, and drive customer experience optimizations.

The Data Engineer will build and maintain scalable data pipelines, improve ETL processes, collaborate with AI/ML teams, and contribute to engineering culture.

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

Work across data infrastructure and analytics: build and maintain dbt models, ingest and transform data, create dashboards and semantic layers in Power BI, validate AI-generated code, partner with stakeholders to deliver analyses and data products, and improve data governance and documentation.

Build and maintain revenue and customer-lifecycle reporting, author complex BigQuery SQL, develop segmentation and clustering models in BigQuery ML, perform entity resolution and data quality reconciliation, migrate and maintain Tableau dashboards, and deliver ad-hoc and recurring analyses to support Sales, Revenue, and cross-functional teams.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.