Top Data & Analytics Jobs in Ogden, UT

Lead and scale the data engineering team to design, implement, and maintain cloud data warehouses, robust ETL/ELT pipelines, data sharing/integration, and BI tooling. Drive roadmap prioritization, recruitment, best practices, governance, and cross-functional collaboration to deliver secure, compliant data solutions that enable analytics and product teams.

The Staff Financial Analyst will manage budgeting and forecasting, develop financial models, automate reporting, and collaborate across departments to enhance financial operations.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Analytics Engineer will build data models and pipelines, ensure data quality, and enable self-service analytics across the organization.

The Business Analyst will gather requirements from clients, support project lifecycles, conduct demos, and manage change, while utilizing ServiceNow. Responsibilities include documentation and relationship building.

As a GTM Engineer, you will improve the efficiency of Marketing and SDR teams through automation, AI, and workflow design. You will partner with various teams and take ownership of the solution lifecycle from discovery to delivery.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.

The Financial Data Analyst will own financial reporting and analytics, manage budgets, develop KPIs, and ensure accurate financial metrics for leadership decision-making.

The Director of Analytics leads a team to generate insights using healthcare data, supports product development, and engages with clients, leveraging advanced analytics to inform decision-making.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.