Top Remote Data & Analytics Jobs in Provo, UT

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Designs, develops, deploys, and supports enterprise business intelligence solutions using Power BI and related visualization platforms. Builds semantic and dimensional models, dashboards, reports, and analytical solutions; applies statistical techniques to identify trends and performance drivers; and translates findings into recommendations. Partners with stakeholders and data engineering teams, establishes reporting standards, optimizes performance, supports modernization and certification, and provides technical guidance. The senior level may lead complex initiatives, review designs, and mentor analysts.

Conduct research and quantitative analysis related to law school access, affordability, academic and bar success, and legal education value. Clean and organize data, maintain research tools and repositories, create statistical tables and visualizations, advise stakeholders on research methods and data interpretation, and produce briefs, reports, and presentations for policy and practitioner audiences.

Supports railroad commission reporting and data publishing initiatives by gathering requirements, analyzing data and errors, documenting processes and data flows, developing Power BI reports with Snowflake, coordinating open-data publishing, and supporting user acceptance testing, training, implementation, and special projects.

Serves as the technical authority for Azure SQL architecture, deployment, security, performance, operations, and migrations supporting federal programs. Designs secure Azure Government database environments, leads on-premises SQL Server migrations, develops T-SQL and data models, builds Azure Data Factory pipelines, implements DevOps and infrastructure automation, troubleshoots incidents, optimizes costs, documents standards, and mentors team members. Collaborates with engineering, architecture, data, and DevOps teams on reliable data platforms.

Build and maintain Power BI dashboards, reports, data models, and SQL-driven datasets supporting marketing and operations decisions. Analyze funnel, conversion, cohort, channel, ROI, LTV, and forecasting performance; validate data across advertising, CRM, and web analytics sources; and identify actionable insights. Contribute to Databricks pipelines, AI-enabled analytics, experimentation, and marketing mix modeling while partnering with stakeholders to deliver accurate, timely, self-service reporting.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

Supports clients and internal stakeholders by gathering requirements and developing business intelligence, reporting, automation, and low-code/no-code solutions. Creates SQL-based data solutions, reports, dashboards, and visualizations; troubleshoots data and automation issues; and collaborates with infrastructure and development teams to maintain solution stability, performance, and security.

Build and maintain reliable data pipelines supporting money movement, fraud response, and client reporting. Integrate internal and external APIs, orchestrate workflows with Airflow on Kubernetes, and implement testing, monitoring, alerting, and observability. Debug production issues, document root causes, improve pipeline efficiency, collaborate with stakeholders, and contribute to technical designs. The role requires Python, SQL, Airflow, Snowflake, dbt, and GCP experience, with opportunities for increased end-to-end ownership.