Top Senior Analysis Reporting Jobs in Salt Lake City, UT

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

Design, build, and maintain scalable Power BI reports and data models. Reconcile and validate data across Power BI, Salesforce, SAP, and Excel. Partner with stakeholders to deliver data-driven insights, mentor junior analysts, and lead initiatives to improve data quality and reporting consistency.

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 extraction, analysis, and reporting of institutional data to generate actionable insights. Build dashboards and visualizations, perform ad-hoc and complex analyses, collaborate with Data Engineering on ETL/ELT pipelines, document data models, define data standards, and present findings to stakeholders to drive decisions and improve data quality and operational outcomes.

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.

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.