Top Senior Analysis Reporting Jobs in Salt Lake City, UT

Leads business intelligence and operations analytics for frontline, backline, workforce management, and customer experience teams. Builds scalable Tableau reporting frameworks, defines KPIs and data requirements, analyzes operational datasets, and performs root-cause investigations. Translates findings into recommendations for process improvement, workforce planning, and member experience. Partners with engineering, product, data science, and business leaders while using AI tools to accelerate analytics and mentoring junior analysts.

Build and maintain ETL/ELT pipelines to move product data into analytics-ready stores (Postgres, data lake, warehouse). Design and optimize data models, ensure data quality and documentation, support ad-hoc research requests, and collaborate with research and engineering teams to enable reproducible analytics.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Designs scalable data architectures, ELT/ETL pipelines, data models, quality frameworks, and self-service data platforms. Partners with engineering, product, program, leadership, and data science teams to translate business needs into technical solutions. The role includes end-to-end technical ownership, large-scale batch and streaming data processing, mentoring junior engineers, system optimization, and on-call support for platform stability.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Own data pipelines into and out of the warehouse, dbt models, data integrity, governance, identity resolution, reverse ETL, and quality monitoring across growth, lifecycle, and brokerage data. Partner with product, marketing, and operations teams to establish data contracts, ensure accurate and timely business metrics, and support regulated financial data requirements.

Staff Data Engineer responsible for setting technical direction, architecting scalable data platforms, leading cross-functional initiatives, improving reliability and performance, and enabling AI-assisted analytics and development. The role includes hands-on development with Python, SQL, cloud data warehouses, orchestration, infrastructure as code, Kubernetes, Kafka, and streaming pipelines, along with mentoring, technical advocacy, documentation, code reviews, and on-call troubleshooting.

Analyzes account portfolio whitespace, pipeline, deal performance, campaign attribution, rep productivity, budgets, forecasts, and expenses. Builds models and executive reporting to improve revenue planning, forecast accuracy, and account management decisions. Partners with Account Management, Finance, Marketing, Contract Administration, and regional leaders; validates Salesforce data and translates complex findings into actionable recommendations.

Leads Motorsports Data Infrastructure and Data Science teams while owning the strategy, architecture, and delivery of data platforms supporting telemetry, simulation, trackside, analytics, and AI/ML use cases. Responsibilities include managing managers, designing streaming and batch pipelines, productionizing ML models, setting engineering standards, managing Azure and Databricks capacity, protecting sensitive data, and partnering with racing and executive stakeholders. The role remains hands-on in architecture, coding, code review, incident support, and technical problem-solving.

Build and maintain dbt data models, SQL transformations, ingestion pipelines, orchestration, and Tableau dashboards in support of HR and enterprise analytics. Own data quality, metric standardization, privacy controls, Row-Level Security, documentation, CI/CD, and troubleshooting from source systems through reporting. Partner with stakeholders to define requirements and KPIs, support workforce forecasting, optimize BigQuery performance, and pilot AI-assisted analytics using Google Gemini.

Own marketing measurement from initial engagement through closed-won revenue. Manage cross-channel reporting tied to Salesforce pipeline, tracking across GA4, advertising platforms, SEO, and AI search. Validate multi-touch attribution, analyze marketing experiments, model budget impact, and recommend investment priorities. Present performance insights to marketing and sales leadership across global regions.