Top Analysis Reporting Jobs in Ogden, UT

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Design and maintain analytical data models, transformation frameworks, data-quality checks, semantic definitions, and metric consistency across analytics and customer-facing products. Partner with engineering, product, and analytics teams to document data, improve lineage, and enable trustworthy self-service data usage. The role requires advanced SQL, analytics engineering, dimensional modeling, testing, and collaborative translation of business concepts into precise data definitions.

Lead the architecture and development of Vercel’s next-generation data platform, supporting batch and real-time integrations, analytics, data warehousing, and AI/ML workloads. Design scalable systems using Kafka, ClickHouse, Tinybird, and Snowflake; establish data governance and security standards; guide architectural decisions and roadmaps; collaborate with engineering, product, security, compliance, and leadership teams; write production code; and mentor engineers.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Own actuarial models and client-facing reporting measuring cost savings, outcomes, and performance of healthcare prior authorization programs. Analyze authorization and claims data, conduct impact evaluations, reconcile projected and realized results, investigate trends, and present executive-level insights to customers and leadership. Partner with clinical, customer success, data, and actuarial teams while maintaining reproducible, auditable methodology and documentation.

Leads Data Engineering, Data Governance, and BI/Analytics teams while owning enterprise data platform architecture, pipelines, governance, warehouse or lakehouse design, BI strategy, and data quality. Serves as the technical bridge between data teams and business stakeholders, manages the platform roadmap, and oversees governed data integration for Glean AI search and agent tools. This hands-on director role combines architecture, engineering, people leadership, strategic planning, and stakeholder partnership.

Analyze and transform cloud data using SQL, dbt, and Google Cloud; build automated pipelines, data visualizations, validation checks, unit tests, monitoring, and alerts. Partner with engineering teams and enterprise insurance clients to improve data quality, governance, automation, and decision-making. Communicate insights clearly, document technical work, develop insurance domain expertise, and contribute to collaborative reviews and on-call support.