Top Data & Analytics Jobs in Salt Lake City, UT

Design, build, optimize, and modernize enterprise Microsoft data platforms (Azure, Fabric). Develop ETL/ELT pipelines, data warehouses/lakehouses, implement governance, security, DevOps/CI-CD, and support Power BI and AI initiatives while consulting with stakeholders.

The Innovations and AI Solutions Engineer develops and optimizes AI solutions, manages data flows, implements machine learning models, and collaborates with users on data analysis and reporting.

Support pricing and fleet availability decisions by analyzing pricing, fleet, and market data, preparing reports and dashboards, monitoring competitor pricing and demand, maintaining data integrity, and collaborating on revenue management initiatives.

The role focuses on bridging business needs and IT solutions, improving processes, managing technical support, and facilitating communication between stakeholders. Requires Spanish fluency.

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

Manage day-to-day pricing operations and reporting across multiple banners: pull data from the warehouse, run competitive audits, execute price changes, track MAP/MSRP compliance, build dashboards, use AI to automate workflows, and recommend pricing actions to improve sell-through, margin, and working capital.

The Product Analyst will conduct data analysis, identify trends, and communicate insights to support product-driven decisions, ultimately driving revenue for partners.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

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).

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.