Top Senior Analysis Reporting Jobs in Salt Lake City, UT

Design, build, and optimize scalable data pipelines, ETL/ELT processes, and data architectures. Develop dimensional models and semantic layers, ensure data quality and integrity, maintain data warehouses and lakes, collaborate with stakeholders to translate requirements, document solutions, and support analytics using platforms like Databricks, Snowflake, DOMO, and Fabric.

The Business Systems Analyst evaluates processes, analyzes requirements, manages projects, liaises with stakeholders, and develops data reports and solutions.

Technical lead for data engineering who designs, builds, and owns scalable Snowflake ELT pipelines and data models. Mentors engineers, drives standards, optimizes performance and costs, and partners with product, analytics, QA, and governance to deliver observable, high-quality data solutions. Contributes to platform strategy, DataOps/CI/CD adoption, and ensures data quality, testing, and documentation.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Lead digital analytics and measurement strategy for web and mobile, design and implement scalable measurement solutions (Adobe stack), build data layers and event schemas, implement JavaScript-based tracking, ensure data quality, analyze A/B tests, and partner with Product, Engineering, Marketing, and Data teams to drive actionable insights and improvements.

The Senior Data Analyst gathers business and analytics requirements, evaluates internal and external data sources, and ensures data quality, governance, lineage, and validation. The role maintains data dictionaries and master data, defines KPIs, reconciles dashboards, documents data transformations, identifies automation opportunities, and delivers actionable insights. It also supports privacy controls, disaster recovery requirements, platform cost optimization, stakeholder communications, and mentoring of less experienced team members.

Leads enterprise data engineering initiatives by designing and optimizing data pipelines, data lakes, warehouses, and analytics infrastructure. Uses Snowflake, Informatica, SQL, and related technologies to integrate diverse data sources, improve data quality, secure PII, and support analytics and data science teams. Establishes governance, monitoring, scalability, performance, and cost-efficiency practices while mentoring teammates and partnering with stakeholders on complex technical solutions.

Manage enterprise BI and analytics platforms, data governance, access controls, and self-service reporting. Translate business requirements into governed dashboards, KPIs, metrics, and actionable insights using Power BI, Tableau, Azure, SQL, and multiple database technologies. Ensure data quality, platform scalability, business continuity, cost efficiency, and secure information delivery. Partner with business and technology stakeholders, lead process improvements, resolve complex issues, and mentor data professionals.

Leads data and analytics engineering for Zero Trust maturity assessment and implementation measurement. Designs common data models, integrates and validates enterprise data, develops maturity and risk metrics, supports prioritization and gap analysis, and establishes data quality, lineage, traceability, and documentation practices. Partners with dashboard and automation specialists to streamline reporting and data refresh workflows.

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.

Design, build, and maintain data pipelines, dashboards, and predictive models. Analyze large datasets to generate actionable insights, collaborate with stakeholders, ensure data quality and governance, and document/share analytics best practices to support Marketing, Product, Operations, and Workforce teams.

Analyze large datasets, build SQL queries and data pipelines, develop predictive and statistical models, create dashboards, ensure data quality/governance, and translate insights into actionable recommendations for Marketing, Product, Operations, and Workforce teams.

Analyze large, complex datasets to generate actionable insights; build SQL queries and data pipelines; develop predictive models (regression, clustering, forecasting); create and maintain dashboards; ensure data quality and governance; collaborate with stakeholders to translate findings into business recommendations and document work.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.