Top Senior Analysis Reporting Jobs in Salt Lake City, UT

Leads long-range workforce and resource planning for contact center operations. Owns demand forecasting, staffing, capacity, headcount, cross-skill, and scenario models across business lines and channels. Develops advanced predictive and prescriptive analytics, performance metrics, and decision-support tools using complex data sets. Advises executives on resource allocation, service levels, costs, and business performance while governing data quality and analytical processes. Leads capacity planning analysts and drives continuous improvement through automation, machine learning, and improved forecasting methodologies.

Performs advanced SQL analysis of large datasets to evaluate marketing ROI, campaign and channel performance, customer behavior, attribution, retention, and conversion. Develops KPIs, dashboards, business cases, experiments, and analytical recommendations while identifying data quality issues. Partners with Marketing, Analytics, Data Engineering, Product, and Technology teams and communicates findings to technical and business stakeholders.

Leads enterprise data governance operations and Cambia’s data platform governance, including stewardship, metadata, data quality, classification, lineage, and semantic-layer governance. Develops policies and standards, ensures regulatory compliance, improves processes, tracks KPIs, and builds AI-ready data foundations. Manages employees and contractors, partners with IT, Security, Compliance, Privacy, and business stakeholders, and executes strategic governance plans while contributing hands-on to technical deliverables.

Leads decision support and data analysis projects, translating business requirements into reporting applications and analytical solutions. Develops complex programs using SAS, R, SQL, and database technologies; models data sources and flows; creates analytical methods and performance measures; interprets statistical results; and presents recommendations to stakeholders. Mentors colleagues, supports data governance and security frameworks, and consults with internal and external business partners.

Designs and builds scalable batch and real-time data pipelines, ingestion workflows, analytical systems, data products, and intelligent APIs. Ensures data quality, reliability, and performance while supporting cloud-based data architecture for BI and AI/ML use cases. Collaborates with cross-functional teams, participates in code reviews, and follows DevOps and CI/CD practices using Databricks, Spark, Python, SQL, and Azure services.

Build and operate scalable AWS batch and streaming data pipelines, event platforms, data quality frameworks, warehouse models, and ML feature infrastructure. Support personalization, recommendation, AI, experimentation, and model-serving workflows while optimizing Redshift performance. Lead technical architecture, establish engineering standards, mentor engineers, and collaborate with product, analytics, data science, and ML teams.

Analyze paid marketing performance across channels, campaigns, audiences, and creatives from initial click through funded deal. Build quality and funnel metrics, evaluate experiments, validate attribution and data quality, develop dashboards, and communicate actionable recommendations to marketing and executive stakeholders. The role uses SQL, Python, marketing platforms, web analytics, and AI tooling to optimize acquisition efficiency and funded-customer outcomes.

Own product analytics for the Accounts Payable product, setting the analytics agenda, defining metrics and OKRs, identifying product opportunities, and influencing roadmap decisions. Responsibilities include experimentation, causal inference, executive reporting, production-grade dbt models, data quality validation, documentation, and AI-assisted workflow automation. The role partners closely with Product, Engineering, and AP leadership and requires confidently presenting insights to senior stakeholders.

Lead data engineering projects by designing scalable data solutions, pipelines, ETL processes, cloud-native applications, and ML-enabled analytical tools. Responsibilities include architecture design, code reviews, CI/CD, documentation, mentoring engineers, client engagement, proposal support, and collaboration with consulting teams. The role requires strong Python, SQL, cloud, big-data, orchestration, and DevOps expertise, with international client travel as needed.

Lead data engineering initiatives involving large-scale data solutions, cloud-native applications, ETL pipelines, data architectures, CI/CD, and machine learning deployment. The role includes mentoring engineers, ensuring code quality, documenting operational processes, supporting consulting teams, engaging clients, contributing to proposals, and delivering analytics solutions globally. International client travel may be required.