Top Senior Analysis Reporting Jobs in Ogden, UT

The Solutions Architect will lead the creation of AI-driven tools and data models, partnering with teams to transform complex datasets into actionable insights and developing robust dashboards and frameworks to empower business solutions.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

Lead a small BI team while remaining hands-on: write advanced SQL, build dashboards and models, enable self-service analytics, set governance, surface insights for stakeholders, and shape a BI roadmap that scales with alerting, anomaly detection, and applied AI/ML.

The Sector Lead for Financial Services will oversee channel research projects, ensuring quality and relevance while guiding a team of analysts. Responsibilities include developing questionnaires, managing research workflows, and expanding coverage across financial services sectors.

The Manager of Analytics oversees a team to deliver impactful analytics and insights, supports business decisions, and integrates AI applications in analytics. They also manage testing portfolios and develop actionable insights for marketing strategies.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

The Lead Product Analyst will design experiments, ensure data quality, build dashboards, and create an experimentation framework focusing on growth and product metrics.

The Senior Consultant will lead the design and implementation of data solutions using Microsoft Fabric, Power BI, and Databricks to enhance analytics capabilities for clients. They will engage with stakeholders to define data strategies and deliver high-quality consulting services across multiple projects.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

Lead design and delivery of a scalable, multi-product data platform. Architect and build robust batch and streaming pipelines, modernize legacy systems, improve observability, and partner with product, data science, and engineering to enable AI-driven solutions at scale.