Top Data & Analytics Jobs in Salt Lake City, UT

Analyze contributor performance, dataset quality, production efficiency, and client delivery metrics. Build dashboards and reports, conduct cohort and trend analysis, monitor quality benchmarks, identify data integrity issues, and translate findings into actionable recommendations. Collaborate with Data Operations, Engineering, Product, and Quality Assurance teams to define metrics and evaluate improvements.

Lead BI developer owning end-to-end reporting for marketing verticals. Build and standardize dashboards, model complex/third-party data (LookML), partner with Yield, Paid Media, and Account Management to deliver actionable analyses that optimize campaign performance, conversion, and revenue.

Build and maintain production ETL/ELT pipelines, data models, and curated datasets for analytics and AI applications. Ingest data from databases, APIs, SaaS tools, and event streams; implement quality checks, monitoring, documentation, governance, and access controls. Collaborate with analysts, data scientists, and ML engineers on reporting, feature datasets, AI search, and RAG applications. Optimize query performance and pipeline costs while using Git, code reviews, and CI/CD for safe releases.

Build and operate event-driven data pipelines processing healthcare claims data for fraud, waste, and abuse detection. Operationalize validated fraud signals, maintain alert delivery and partner dashboards, monitor pipeline reliability, and collaborate with data architects, scientists, and investigative teams. The role requires production-scale pipeline engineering using AWS, Snowflake, Python, and SQL in a fully remote environment.

Own and evolve UJET’s data platform, including MySQL CDC replication to BigQuery, dbt transformations, Terraform infrastructure, pipelines, data quality, observability, and Looker models. Build reliable, analytics-ready datasets and trusted metrics for internal and customer-facing reporting. Partner with Analytics, Finance, Product, and Engineering to deliver scalable data solutions, improve platform reliability, optimize performance and costs, and establish development standards and guardrails.

Supports public health data extraction, management, quality assurance, cleaning, validation, harmonization, documentation, and statistical and qualitative analysis. Develops analytic datasets and evaluates program implementation, reach, fidelity, dose, adaptation, and outcomes. Integrates mixed-methods data, interprets findings, prepares technical memoranda, reports, presentations, tables, and figures, and communicates recommendations to program stakeholders. The role also uses Microsoft Office and CDC administrative systems and requires obtaining and maintaining customer clearance.

Designs and maintains scalable data architecture, warehouses, ETL/ELT pipelines, and data platforms. Responsibilities include ensuring data quality, integrity, governance, accessibility, reliability, and performance; supporting customer onboarding and analytics tools; contributing to architecture and engineering best practices; troubleshooting complex data issues; and participating in on-call rotations. The role collaborates with engineering, product, solutions, business intelligence, and other cross-functional teams in healthcare and social care data environments.

Build and maintain invoicing, reimbursement, revenue recognition, claims, and financial reporting models using SQL and dbt. Reconcile merchant, operational, warehouse, and accounting data; investigate variances; validate expenses; and establish automated financial controls. The role also triages data issues, investigates production APIs, supports audits, partners on merchant configuration, and drives upstream fixes through root-cause analysis and automation.

Leads enterprise analytics strategy, measurement frameworks, KPI development, dashboards, reporting, and insights for B2B commerce, marketing, and customer experience clients. Oversees analytics implementations across web, commerce, CRM, CDP, BI, and data platforms; mentors analysts and consultants; manages data quality and governance; leads executive client discussions, workshops, proposals, and business growth opportunities.

Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.