Top Analysis Reporting Jobs in Provo, UT

Support managed-service customers by administering production Oracle databases, including monitoring, backup and recovery, maintenance, patching, upgrades, performance troubleshooting, security, and high-availability solutions. Assist with installations, automation, documentation, incident and change management, and availability and capacity reporting. The role is customer-facing and involves supporting Oracle environments across on-premises and cloud platforms while developing Database-as-a-Service capabilities under senior DBA guidance.

Design, build, and lead a scalable, configuration-driven data integration platform. Improve performance, automate monitoring and deployments, provide escalated support, and collaborate across product and engineering to deliver reliable, secure data integrations.

Build and own workforce capacity, forecasting, and scenario models that guide hiring, coverage, account assignments, and organizational design. Maintain executive-ready dashboards and real-time visibility into workforce supply, demand, hiring pipelines, utilization, attrition risks, and workload distribution. Partner with HR, Finance, Revenue Operations, and business leaders to translate complex workforce data into actionable decisions and ensure consistent reporting and assumptions across systems.

Serves as a strategic analytics partner to Marketing, owning funnel, attribution, ROI, account scoring, experimentation, and pipeline analytics. Builds scalable datasets, dashboards, and quality controls while connecting customer, campaign, product usage, CRM, and revenue data. Delivers executive-ready reporting, QBR insights, and recommendations that improve conversion, marketing investment effectiveness, account-based marketing, product adoption, and pipeline growth.

Design and maintain scalable ETL/ELT pipelines, analytical dashboards, and reporting tools supporting clinical, research, and operational priorities. Write production-quality Python, R, and SQL; develop data architecture; partner with data scientists to operationalize analytics; integrate AI-enabled workflow improvements; establish engineering standards; and mentor junior team members.

Supports, maintains, troubleshoots, and optimizes production Databricks applications, Spark jobs, SQL queries, Delta Lake pipelines, clusters, workflows, and data quality processes. Responsibilities include platform configuration, observability, documentation, deployment support, technical testing, finance data engineering, stakeholder coordination, and incremental improvements. The role also contributes to reporting enablement, operational readiness, process improvement, and on-call support during EST business hours.

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.

Analyze performance marketing data, including traffic quality, unit economics, reporting, attribution, A/B testing, forecasting, and monetization. Build dashboards, anomaly alerts, and data models using BigQuery, dbt, and Tableau. Partner strategically with performance teams to identify growth opportunities, improve channel evaluation, and guide scaling decisions through SQL, Python, and statistical analysis.

Analyze marketing performance across paid media, CRM, email, and customer engagement channels. Prepare recurring reports, consolidate data into actionable insights, support client recommendations and optimization strategies, and perform quality checks on reports and datasets. Collaborate with strategy, client services, media, and analytics teams while using AI tools responsibly to improve reporting efficiency.

Analyze complex financial and business data to guide planning, forecasting, investment decisions, and strategic growth. Partner with FP&A, Accounting, RevOps, Product, Marketing, Data Engineering, and analytics teams; automate recurring workflows; build self-service dashboards and data assets; improve analytics infrastructure; and communicate actionable insights to technical and non-technical stakeholders.