Top Data & Analytics Jobs in Provo, UT

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Designs, builds, and operates scalable batch and real-time data infrastructure processing trillions of data points. Responsibilities include platform architecture, infrastructure as code, self-healing systems, observability, developer tooling, pipeline optimization, security controls, database tuning, and distributed-system troubleshooting. The role collaborates with engineering and product teams, improves reliability and performance, and enables safe access for data engineers, software engineers, and AI agents.

Leads fraud strategy through trend analysis, root-cause investigation, mitigation recommendations, and fraud-control optimization. Manages and mentors 2–5 fraud analysts, evaluates detection tools and data sources, monitors performance metrics, and communicates risk insights to leadership. Partners with Operations, Compliance, Credit, and Product teams to implement compliant fraud strategies and reduce losses while supporting growth.

Own contact center KPI analysis covering volume, handle time, adherence, occupancy, and service level. Build Tableau or Power BI dashboards, identify trends and root causes, and provide actionable recommendations to operational leaders. Manage multiple analytical projects, prioritize changing requests, influence stakeholders without direct authority, and communicate findings through data storytelling. Use AI tools responsibly to accelerate analysis while maintaining data quality, compliance, and human judgment.

Design, implement, and maintain cloud-based data pipelines; integrate disparate data sources; optimize data lakes/warehouses and Spark workflows; automate Quote-to-Cash/Quote-to-Fulfillment processes; collaborate with platform, analytics, and business stakeholders to deliver scalable, reliable data solutions while ensuring data quality and security.

Leads and mentors data engineering teams while remaining hands-on with technical execution. Responsibilities include designing and operating large-scale data platforms, pipelines, integrations, APIs, streaming and batch processing, and high-volume analytics environments. The manager partners with Product and senior leadership on strategy, removes delivery roadblocks, recruits and develops talent, and advances engineering practices, reliability, security, compliance, and scalability. The role is remote within the United States with up to 10% travel.