Top Senior Analytics Jobs in Salt Lake City, UT

Build scalable GTM and product analytics to inform revenue, retention, and growth decisions. Partner with Sales, Customer Success, Finance, Product, and Data Engineering to deliver dashboards, models, and executive data stories; validate data quality; measure ROI; and enable self-service reporting across the lead-to-quote-to-cash journey.

Design, build, and maintain ETL/ELT pipelines and analytics data models from structured and event-level data. Transform clickstream/telemetry into user-level journeys, implement dbt transformations in a cloud warehouse (Redshift/Snowflake/BigQuery), develop reverse ETL workflows, enforce CI/CD/version control and automated data quality tests, and partner with BI, marketing, and product to deliver dashboards and attribution reporting.

Design and maintain a formal analytics data layer (AWS Glue, Athena/Presto, LookML); build data models, pipelines, and automated quality checks; investigate anomalies; document metrics and lineage; mentor analytics team members and promote best practices.

Own and build scalable analytics models, metric definitions, and dashboards (customer-facing and internal). Partner with engineering to design data flows and instrumentation (BigQuery, S3, PostHog). Translate stakeholder needs into analytics plans, triage requests, and surface insights via Looker/Observable. Set analytics stack direction and ensure data quality.

Lead complex analyses of large healthcare datasets to evaluate growth opportunities, measure test-and-learn results, build dashboards and automated reports, enable self-service analytics, and present actionable insights and recommendations to stakeholders to drive pharmacy prescriptions and immunizations growth.

Execute underwriting and case-valuation analytics: write and optimize SQL, build dashboards, maintain valuation models, forecast case outcomes, monitor portfolio performance, and translate insights for operational and marketing stakeholders.

Lead embedded BizOps analytics for a core business area (growth, product, AI, or partnerships). Define problems, build metrics, reports, experiments, and analyses, and drive data-informed recommendations end-to-end to influence leadership and deliver measurable business outcomes.

Own the end-to-end analytics function embedded in a core business area (growth, product, AI, partnerships). Define problems and metrics, build reports, run analyses and experiments, surface insights, make recommendations, and drive outcomes with cross-functional teams.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

Lead a centralized Decisioning Analytics team to measure and optimize Pega-powered Next-Best-Action decisioning. Own measurement frameworks, ADM performance, transparency, governance, cross-functional partnerships, NBA analysis, roadmap, and team development to drive measurable customer and financial outcomes.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

Lead analytics for Omnichannel retail/restaurant/CPG partners: act as primary analytics contact for Sales, manage analytic engagements and team capacity, perform SQL-based analysis, craft data-driven narratives and recommendations, influence campaign strategy, represent analytics in cross-functional settings, and automate insights using AI-enabled tools.

Lead design and delivery of Workday reporting and analytics for AMS clients: build advanced/matrix/trending/composite reports, dashboards, Discovery Boards, Worksheets, and complex calculated fields; gather requirements, optimize reports, mentor junior consultants, and provide Workday best-practice guidance.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Design, build, and maintain production ETL/ELT pipelines, analytics-ready data models, and cloud data infrastructure. Improve pipeline performance, data quality, governance, and migrate legacy systems to modern platforms. Collaborate with stakeholders to translate business requirements into reliable data products for project, financial, and operational analytics.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

As a Senior Analyst, you will develop data-driven solutions in collaboration with operations teams and deliver insights through reports and dashboards to improve patient outcomes.

Design and implement end-to-end Microsoft Fabric data solutions (ingestion, Lakehouse, warehouse, real-time). Create architectures, reusable frameworks, and governance patterns for insurance datasets. Lead ingestion pipelines, optimize performance/cost, integrate with Azure services and security, support regulatory compliance, and provide technical direction to engineering and analytics teams.