Top Data & Analytics Jobs in Provo, UT

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

The Data Migration Specialist will ensure successful data transitions from legacy systems, engage in ETL processes, and provide customer support throughout the migration journey.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Support national community lending initiatives by developing ROI dashboards, analyzing event and CRM data, coordinating events and partners, enabling sales teams, managing budgets/contracts, and producing program performance insights to scale community outreach and homeownership programs.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

Own end-to-end data pipelines for multiple clients: extract, clean, transform, model and visualize data. Build dashboards and automated workflows, apply AI where useful, and present actionable insights to non-technical stakeholders.