Top Data & Analytics Jobs in Salt Lake City, UT

Lead a team of data engineers and BI developers to deliver scalable sales analytics, forecasting, and AI-enabled insights. Set strategy, prioritize roadmap, ensure platform stability and usability, translate business needs into dashboards and reporting, and partner cross-functionally to drive adoption and continuous improvement.

Design, develop, and monitor large-scale data pipelines and cloud-native data applications; collaborate with consulting teams and clients; apply best practices (TDD, CI/CD); build and operationalize ML-ready data platforms; produce documentation and runbooks; mentor junior engineers and contribute to proposals and analytics assets.

Design and run causal inference and impact analyses, build statistical and predictive models, extract and clean multi-source data with SQL/Python/R, troubleshoot data quality, and present actionable insights to cross-functional stakeholders to inform course design and learner success.

Provide Oracle DBMS consulting: architect and design database solutions, optimize and write SQL, benchmark performance and present findings, use code versioning (Git/SVN), perform basic Unix/Windows administration and system monitoring. 6+ month contract in West Valley City, UT.

Design and maintain CS analytics infrastructure: dashboards, reporting, risk/predictor scores, ad-hoc analyses, data dictionaries, and integrity processes. Partner cross-functionally to extract actionable customer insights, forecast, and scale CS data capabilities.

Lead design and execution of benchmarking studies: collect and normalize data, build reusable benchmarking models, define peer cohorts, produce client-ready slide decks, translate gaps into ranked recommendations, maintain repositories, and coach junior analysts.

You will build and operate a validated data platform, ensuring data integrity, mentoring team members, and collaborating on data discoverability and queryability.

The Analytics Engineer will design data models, maintain analytics pipelines, document data governance, and partner with stakeholders to address data needs.

Designs and implements scalable real-time and batch data pipelines, optimizes performance and reliability, applies ML libraries and quantitative methods, builds cloud-native AWS data platform components, develops CI/CD and orchestration, performs testing/validation and documentation, and collaborates on data-centric initiatives in a financial services environment.

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.