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

The Data Strategy & Sourcing Analyst transforms product data into a strategic asset, ensuring data integrity and driving cost savings through sourcing. Responsibilities include establishing a Single Source of Truth, conducting data analysis, and collaborating with teams for financial impact. The role requires strong analytical skills, proficiency in SQL, and experience with data management tools.

Build and maintain reliable data pipelines, Airflow DAGs, and Snowflake-based Data Vault/warehouse models. Implement CI/CD, automated testing, observability, and production support while partnering with stakeholders and developing insurance domain expertise.

The Staff Analyst will design analytical frameworks, lead business case development, and provide insights across departments while mastering insurance analytics.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Design, build, and maintain scalable cloud-native data pipelines, microservices, and AI-driven orchestration. Develop Python APIs (Flask/FastAPI), implement advanced SQL transformations (BigQuery), integrate LLMs/agents for automated workflows, and collaborate with Data Science and Product to deliver production-grade, observable, and secure AI-enabled data solutions.

Translate health plan data into actionable insights using analytics and visualization tools. Collaborate across teams to manage client and broker requests, become a subject-matter expert on internal analytics tools, perform statistical analysis, and communicate findings to improve client plan performance.

Support data and reporting needs by gathering specifications, creating data sets, operational reports, and dashboards. Collaborate with teams to translate business needs into requirements, test deliverables, analyze data for issues and opportunities, manage defects, and ensure quality and compliance throughout the data delivery lifecycle.

Lead onboarding, mapping, and validation for a Customer Data Hub: write user stories and acceptance criteria, define mastering/transformation logic, perform data lineage and reconciliation, validate integrations and outcomes, support production incidents, create runbooks and documentation, and partner with product, engineering, QA, and governance teams to enable reliable customer data for applications and analytics.

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

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.

Work across data infrastructure and analytics: build and maintain dbt models, ingest and transform data, create dashboards and semantic layers in Power BI, validate AI-generated code, partner with stakeholders to deliver analyses and data products, and improve data governance and documentation.