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

Analyze user behavior data to identify friction points, recommend changes for conversion optimization, and collaborate with teams to improve user flows through data-driven insights.

Lead the development and implementation of data architecture strategies, mentor a team to deliver solutions, and collaborate with stakeholders to enhance resources while ensuring project success and quality outcomes.

Lead architecture and delivery of SoFi's data platform: build scalable data pipelines, drive cloud-native and AI-enabled tooling, enforce governance and security, mentor senior engineers, and support production on-call.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

The Technology Governance Automation Engineer enhances compliance and governance processes through automation, data analysis, and collaboration with various teams to ensure efficient and auditable operations.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.