Top Senior Analysis Reporting Jobs in Provo, UT

Build, scale, and maintain data pipelines and transformation layers to ingest diverse sources, ensure data reliability and freshness, optimize data models and compute, create a semantic layer for self-service analytics, support BI reporting, collaborate with cross-functional leadership, and mentor analysts and scientists on engineering best practices.

Temporary 6-9 month Staff Data Analyst supporting eCommerce and marketing analytics. Lead data-driven projects, define and track metrics, analyze product and web data, build dashboards and automated reports, and provide insights for product teams and brand partners to improve user experience and business performance.

Leads marketing performance measurement across paid media, CRM, web, SEO, owned, and offline channels. Ensures KPI reporting accuracy, develops dashboards, analyzes experiments and attribution, supports forecasting and ROI analysis, and translates marketing data into actionable recommendations. Partners with channel owners, Finance, and analytics teams to improve campaign performance, reporting standards, budgeting, and strategic decision-making. Presents insights to marketing leadership and manages reporting improvements in a fast-paced environment.

Lead analytics for clinical decision support adoption and engagement: define metrics, query event-level usage, build dashboards, analyze funnels and cohorts, partner with product and cross-functional teams, and translate findings into actionable product recommendations to improve adoption and outcomes.

Lead Workday reporting strategy for higher education: design Advanced, Matrix, Composite, and Dashboard reports; implement row-level security and role-based access; partner with HR/Finance/Payroll/Institutional Research; support regulatory and executive reporting; manage testing, validation, and user training while ensuring governance and data standards.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Build and operate batch and near-real-time data pipelines, semantic models, certified measures, APIs, and serving infrastructure for AI-powered decision systems. Responsibilities include data quality, observability, lineage, governance, CI/CD, infrastructure as code, performance optimization, model scoring pipelines, and AI telemetry. Partner with data scientists and business stakeholders to productionize models and deliver reusable, documented data platform capabilities.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Design and build PerfectServe’s unified cloud data platform, including ingestion pipelines, integrations, data models, metrics, and consumer-facing data layers. Establish architecture, engineering, quality, and testing standards; enable safe extraction from production systems; partner with data users; and mentor data engineers. The role requires substantial cloud data platform experience, deep SQL, warehouse expertise, ELT, change-data-capture, AWS, modeling, orchestration, and data quality skills.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, data infrastructure, and complex data models. The role supports analytics partners, develops scalable data warehouse solutions, tunes SQL and databases, troubleshoots production issues, and collaborates with architects, analysts, developers, and stakeholders. Responsibilities include end-to-end project delivery, data modeling, big data engineering, production support, agile planning, and mentoring team members.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, cloud data infrastructure, and complex data models. Supports analytics partners, develops data warehouse solutions, tunes SQL and database performance, troubleshoots production issues, and delivers end-to-end data engineering projects. The role collaborates with architects, analysts, developers, and business stakeholders, applies big data technologies, supports agile delivery, and mentors team members.

This role involves writing user stories, supporting agile team processes, and driving customer discovery to enhance technology solutions for clients.