Top Senior Data & Analytics Jobs in Ogden, UT

Develop and implement commercial data acquisition and governance frameworks. Govern data standards, policies, cataloging, quality, lineage, privacy, and compliance. Evaluate and onboard external data sources, negotiate vendor agreements, and manage third-party data relationships. Lead governance platform deployment, training, change management, KPI development, reporting, and continuous improvement while coordinating Commercial Operations, Analytics, IT, and external partners.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Provide insights and recommendations to improve end-to-end purchase customer journeys across web and app for B2C and B2B. Lead A/B testing and experimentation, ensure accurate data collection and impact measurement, build self-service reporting and visualizations, query and process data, and present findings to stakeholders and senior leadership.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

Lead Databricks-based enterprise data and analytics modernization programs. Define future-state architecture, drive platform modernization, ensure security, scalability, cost optimization, and mentor teams while delivering AI-ready data platforms and governance.

The VP Global Grid Modeling will lead global data strategy, manage high-performing teams, ensure quality datasets, and engage with customers for insights in energy markets.

Client-facing BI consultant responsible for end-to-end delivery of TARGIT-based analytics: requirements gathering, prototyping, backend work, dashboards, training, deployment, optimization, and customer engagement.

Partner with sales leadership to define business requirements, design end-to-end analytics solutions (data models, semantic layers, dashboards), build scalable Power BI/Microsoft Fabric reporting, translate data into executive-ready insights, drive automation and standardization, mentor analysts, and influence business decisions with data-driven recommendations.

Lead research on the macroeconomics of AI by authoring flagship reports, building quantitative forecasting models, integrating bottom-up semiconductor and datacenter data into macro estimates, developing LLM-driven research pipelines, performing econometric analysis, and communicating findings to investors, policymakers, and the public.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.