Top Data & Analytics Jobs in Boise, ID

Lead Cohere’s Data Foundation pillar, managing a team responsible for the full data lifecycle. Own the roadmap, BigQuery warehouse, Airflow and Cloud Run orchestration, dbt modeling, Looker and API serving, Terraform infrastructure, governance, access controls, reliability, incident response, and data freshness SLAs. Lead development of an agentic analytics platform and evaluation framework, establish company-wide analytics standards, and partner with product, engineering, security, legal, and business teams.

Leads Gartner research and thought leadership on data management for AI enablement. Provides expert guidance on data platforms, governance, context-layer architectures, AI integrations, and secure enterprise infrastructure. Develops market insights, advises executive clients, delivers presentations, supports sales, reviews content, mentors analysts, and improves research processes. Requires strong research, writing, analytical, presentation, communication, business, and technical skills, with up to 25% travel.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Designs and owns Databricks lakehouse architecture, scalable batch and streaming pipelines, data governance, analytics models, and cloud infrastructure. Leads major platform migrations, establishes engineering and CI/CD standards, manages Terraform and FinOps practices, and prototypes AI use cases. The role advises stakeholders, mentors engineers, and ensures secure, compliant, cost-effective data platforms across cloud environments.

Designs and optimizes Databricks data pipelines, Spark jobs, clusters, data models, ETL/ELT processes, and Lakehouse architectures. Implements governance, security controls, CI/CD, and cloud integrations across AWS, Azure, and GCP. Advises engineering teams, mentors staff, defines technical roadmaps, collaborates with stakeholders, and troubleshoots Databricks performance and system issues.

Own the go-to-market master data management roadmap and governance model for accounts, contacts, and organizational hierarchies. Define golden record, matching, merging, survivorship, data quality, stewardship, and SLA standards across Salesforce, billing, finance, marketing, product, support, and warehouse systems. Partner with engineering, systems, finance, legal, and security teams to implement integrations, privacy controls, data products, and remediation programs. Report data health, risks, and business impact to leadership.

Supports Navy training readiness analysis, data validation, dashboard and report development, performance metrics, data migration, process improvement, training coordination, and documentation. Uses reporting and visualization tools to support FTM and FLTMPS initiatives within the Jupiter data environment. Collaborates with government stakeholders and contractor personnel while maintaining data governance and security procedures.

Maintains accurate CRM data across HubSpot and ServiceNow by processing data requests, entering and cleaning records, resolving duplicates, managing account relationships, supporting bulk uploads, and addressing cross-system data issues. Partners with Sales, Marketing, and IT Development to ensure accurate integrations, workflows, deal data, and adherence to data processes.

Analyzes business performance data and delivers actionable insights for stakeholders and senior leaders. Develops dashboards, scorecards, KPI reports, and recurring brand reporting while ensuring data accuracy and reliability. Partners with sales, marketing, product, and technical teams to translate business needs into analytics solutions. Performs ad hoc analysis, identifies trends and risks, supports executive presentations, and communicates recommendations clearly.

Architect and lead enterprise data platforms, pipelines, and infrastructure using Spark, Databricks, and cloud technologies. Build scalable data models and dimensional schemas, establish governance and data quality frameworks, optimize performance and reliability, and implement monitoring. Partner with stakeholders to translate requirements into technical solutions, lead design reviews, mentor engineers, contribute to platform strategy, troubleshoot complex failures, and support hiring and team development.