Top Data & Analytics Jobs in Ogden, UT

Performs remote data entry and administrative support by entering, updating, verifying, and organizing information in digital databases and electronic records. Maintains spreadsheets, reviews documents for accuracy, identifies discrepancies, protects confidential information, responds to update requests, and completes assigned projects on schedule while communicating progress to supervisors.

Build and optimize Snowflake data transformations across staging, curated, and conformed layers. Implement dimensional models, SCD Type 2 history, member matching, payer attribution, reconciliation, and member-month outputs. Develop restartable, testable processing with audit logging, error handling, data-quality checks, alerting, and schema-drift controls. Troubleshoot production issues, maintain documentation, participate in reviews and planning, and support client demonstrations.

Leads advanced data analytics and engineering initiatives, including data infrastructure, ETL, pipelines, warehousing, governance, visualization, and AI-enabled solutions. Supervises analysts, manages data systems and Smartsheet workflows, ensures documentation and contract compliance, and delivers insights, reports, and recommendations to improve program operations and grant management.

Analyzes claims data to identify trends, patterns, risks, and business opportunities. Retrieves, validates, and prepares data from multiple databases; creates reports, dashboards, visualizations, spreadsheets, and presentations; supports forecasting and reporting needs; collaborates with claims, underwriting, product, IT, and leadership teams; and communicates recommendations for business decisions and process improvements.

Build Python and SQL data pipelines, maintain data integrity, automate dashboards and reporting, and deliver actionable analytics. Develop AI- and LLM-assisted workflows for data enrichment, classification, summarization, and process automation. Support leadership decision-making, sales, customer success, and internal efficiency while communicating insights to nontechnical stakeholders. Evaluate, document, and monitor AI solutions for accuracy, cost, risk, and auditability.

Designs, develops, deploys, and supports complex enterprise data pipelines, data models, ETL/ELT processes, and analytical solutions. Leads data governance engineering initiatives involving metadata catalogs, lineage, data quality, and remediation. Builds governed, AI-ready datasets and integrates AI capabilities into production data workflows while validating performance, security, privacy, and reliability. Collaborates with business, technology, data science, and application teams to deliver scalable, compliant solutions.

Leads Development’s data and systems operations, including CRM and WeGive administration, platform integrations, data hygiene, reporting, governance, troubleshooting, documentation, and staff training. Manages the Constituent Records Management team and Business Solutions Analyst, oversees vendor relationships, validates system updates, supports donor-data security and compliance, and translates technical issues into operational recommendations for leadership.

Leads sales attribution and incrementality measurement for advertising campaigns using transaction data. Develops causal measurement methodologies, productizes client reporting, advises senior brand and agency clients, sets measurement standards, partners with Product and Engineering on automated pipelines, and grows the measurement team. Requires deep advertising analytics, purchase-based measurement, causal inference, SQL, Python or R, and familiarity with retail media, DSPs, clean rooms, and campaign exposure data.

Lead managed services for clients' Azure, Databricks, and Microsoft Fabric data environments. Architect, implement, monitor, troubleshoot, and govern data platforms, ETL pipelines, data warehouses, semantic models, reporting, and AI/ML solutions. Manage incidents and SLAs, advise clients on licensing and technical strategy, communicate solutions, document environments, and mentor distributed engineering teams.

Analyzes data from multiple sources to identify trends, develop member segmentation and lifecycle models, support competitive analysis, and recommend strategies for improving member participation and financial products. Builds reports, dashboards, and data-driven tools for leaders and staff, collaborates with stakeholders, trains power users, and provides ongoing analytical support using SQL, R or Python, ETL, data modeling, and business intelligence tools.