Top Remote Data & Analytics Jobs in Boise, ID

Design and own end-to-end data models and dbt transformations on BigQuery, maintain the semantic layer in Lightdash, govern metrics, enable AI-assisted analytics workflows, partner with stakeholders to deliver trusted reporting, and lead data modeling standards, testing, and documentation.

Support risk and analytics efforts by performing SQL/Python-based analysis, monitoring portfolio health, building scalable reports, collaborating cross-functionally, and integrating AI tools to surface insights that inform product, risk, and growth decisions.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

The Data Engineer will develop and implement ETL processes, design data architectures, work with data platforms, and ensure data solutions meet scalability and security needs. Responsibilities include mentoring junior engineers and collaborating with stakeholders to gather requirements and optimize data transformations.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

Help new Dynatrace customers adopt Digital Experience capabilities (Synthetic Monitoring, RUM, Session Replay). Perform data-driven analysis, create concise enablement and investigation deliverables, prioritize customer onboarding activities, drive usage expansion, and collaborate with account teams while communicating findings to technical and business stakeholders.

Lead and scale enterprise data governance operations: manage the data domain model and business glossary, run governance council operations, enforce data policies and compliance (SOC 2, GDPR/CCPA), drive catalog adoption and data literacy, and measure governance maturity and ROI through dashboards and remediation workflows.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

Design and automate reporting and workflows for financial operations. Analyze and troubleshoot data pipelines, build reports, collaborate with SMEs to remove manual bottlenecks, and own small optimization projects to improve operational efficiency.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.