Top Senior Data & Analytics Jobs in Salt Lake City, UT

The Senior Manager-Quality Engineering & Automation will lead quality engineering practices, oversee testing frameworks, manage teams, and promote automation and quality excellence in software delivery.

The Workday Integration Lead will design, implement, and manage integrations between Workday modules and other systems, ensuring data integrity and supporting operations.

As a Senior Commercial Insurance Analyst, you'll perform complex analyses on data to drive business performance and risk outcomes. You'll collaborate with various teams, generate actionable insights, and mentor junior analysts, all while fostering a data-driven culture and improving operational efficiency.

Lead requirements gathering and stakeholder engagement, analyze business processes and data, document business requirements, support system implementations and process improvements to deliver operational efficiencies for fund administration and middle-office services.

Hands-on Senior Data Engineer to maintain and optimize an Oracle-centric enterprise data warehouse, manage cloud-to-Oracle integrations, evolve ETL/ELT pipelines, and help build a hybrid lakehouse (Apache Iceberg, OCI Object Storage, Parquet). Requires performance tuning, Linux administration, Java debugging, and close collaboration with senior client stakeholders. Contractor role with possible conversion to full-time.

The Analytics Manager will lead analytics for the Payments and Identity lifecycle, manage a team of analysts, develop KPIs, and ensure data quality while collaborating with cross-functional teams.

Quantitative Researchers at Xantium analyze financial datasets, develop quantitative trading models, and support trading operations. They collaborate with senior staff and enhance their research skills, primarily in mathematics and statistics.

Build and maintain financial and operational models and dashboards linking GTM activity to pipeline and revenue. Perform scenario and variance analyses, produce executive-ready narratives, support cross-functional data integration, and drive improvements to reporting, forecasting, and analytical processes.

Lead fraud detection analytics for payment card transactions: analyze large datasets with Python and SQL, implement real-time detection strategies, support anomaly detection for coordinated fraud, refine rules and models, and communicate insights to influence stakeholders and reduce risk.

Perform root-cause operational analysis across people, process, and tools; mine ITSM data; build Tableau-based dashboards and executive-ready visualizations; collaborate cross-functionally to prioritize efficiency initiatives and present actionable recommendations to leadership.