Top Remote Analysis Reporting Jobs in Salt Lake City, UT

As a Senior Data Engineer, you'll design and maintain scalable data pipelines, optimize workflows with dbt and Snowflake, and mentor teams across functions to enhance data reliability and performance.

The Data Engineer I will build and maintain data pipelines, contribute to platform code, and integrate data sources while growing alongside senior engineers in a production-focused role.

The Senior Manager, Performance Data Operations leads the Population Health Impact team, driving performance improvement initiatives, building complex datasets, and communicating insights to stakeholders. Responsibilities include data analytics, program management, and fostering cross-functional relationships.

The Data Solutions Architect at MANSCAPED will manage the enterprise data architecture, ensure security and scalability, and support BI reporting and advanced analytics.

The Analytics Architect will design and implement cloud-based analytics solutions, maintain data pipelines, ensure data quality, and collaborate with teams to enhance operational efficiency.

Lead end-to-end data migration strategy and execution for complex franchise partners—perform discovery, map legacy data, troubleshoot imports, align stakeholders, and build scalable playbooks to standardize data delivery and ensure seamless platform transitions.

As a Sr. Staff Deployment Strategist, you will drive business transformation by partnering with clients to design and implement AI-powered data intelligence solutions, ensuring value realization and client integration.

Drive enterprise automation by identifying workflow inefficiencies across Home Health, Primary Care, and Pharmacy. Use data analysis, process and journey mapping, and MDM to define opportunities and leading indicators. Partner with product, engineering, clinical, compliance, and operations to design, validate, and scale AI-enabled automation solutions that improve outcomes and efficiency while ensuring regulatory compliance.

Support a Department of State data engineering program: review data policies and governance, define requirements, build and maintain Palantir-based data pipelines, clean and integrate datasets, detect and remediate data fidelity and pipeline issues, produce analyses and visualizations, and coordinate with non-technical users and stakeholders.

Design, build, and maintain scalable data pipelines, data models, ETL/ELT, and BI solutions. Collaborate with data scientists and stakeholders to improve data quality, accessibility, and PHI security. Develop and document workflows, optimize processing/storage, support data warehouse and visualization, and adopt AI tools to drive data-informed outcomes.