Top Data & Analytics Jobs in Provo, UT

Lead product analytics initiatives to optimize product adoption and revenue growth while serving as a trusted thought partner to senior leaders.

Lead and grow an Operations Analytics team to provide KPI insights across Service, Sales, Collections, Banking, and Back Office. Build scalable reporting, financial models, ROI analyses, and tracking for operational improvements. Partner with Finance and senior leaders to prioritize transformation initiatives, ensure data governance, and measure realized financial and operational impact.

Support strategic pricing, packaging, and monetization initiatives through data analysis, financial modeling, and cross-functional collaboration to enhance revenue growth.

As an Analytics Engineer at Podium, you'll build data tooling for sales analytics and operations, create data models on Snowflake, and collaborate cross-functionally to empower teams with data.

The Data Analyst supports teams in making strategic decisions using data. Responsibilities include data analysis, reporting, visualization, and improving processes for better business performance.

The Revenue Data & Insights Analyst role involves building and optimizing sales reporting, managing pipeline processes, providing actionable insights, and maintaining data quality to support sales strategy.

The Business Analyst translates business needs into system requirements, documents requirements, manages multiple projects, and conducts testing for system enhancements and maintenance.

As a Lead Data Analyst, you'll lead complex analyses, manage client analytics partnerships, ensure data integrity and optimize SQL, while delivering actionable insights and influencing decision-making for stakeholders.

As a Senior Data Engineer, you'll design and implement ETL/ELT pipelines, write Python code for data processing, and optimize SQL models. You'll collaborate with teams and improve data architectures to support AI and marketplace strategies.

The Data Engineer is responsible for building ELT pipelines, migrating data to a new EDW, developing data observability processes, and collaborating with teams to ensure data requirements are met while improving data accessibility.