Top Remote Data & Analytics Jobs in Ogden, UT

Build and maintain scalable data pipelines for healthcare claims; implement de-identification and PII-reduction; ensure data quality and observability; integrate data stores and APIs; draft technical designs and documentation; gather product feedback and iterate quickly.

Lead a team to analyze, optimize, and grow merchant revenue using analytics and AI. Define strategy, set KPIs, deploy ML solutions, drive go-to-market alignment, execute tests, and deliver actionable insights to executives and cross-functional partners.

Own pre-sales funnel analytics from lead to closed-won for EverHealth products. Build funnel conversion and pipeline-quality reporting, ICP and win/loss analysis, cohort and TAM analyses, Salesforce dashboards, and actionable insights for Sales, Marketing, and RevOps. Use AI tools to accelerate reporting and support GTM planning, quota modeling, and competitive intelligence.

Lead pricing strategy and analytics: develop pricing, packaging and monetization recommendations; build forward-looking revenue/volume models; maintain pricing algorithms and reporting; collaborate with Sales, Finance, Marketing and Data teams to implement pricing actions and standardize quantitative outputs.

Build and maintain scalable data pipelines and integrations using Databricks and Azure. Transform and model large structured and unstructured datasets to support reporting, analytics, and operational needs. Implement data quality, monitoring, and governance; troubleshoot pipeline performance; collaborate with stakeholders and mentor junior engineers.

Support review of source inventories and cross-reference authoritative port/waterway datasets; design and implement geodatabases and attribute schemas; produce and validate polygons, run topology checks, develop metadata and source lineage, document discrepancies, and support QA and incremental production deliveries.

Design, build, and operate large-scale data pipelines and ETL processes to normalize varied partner datasets. Lead technical decisions, mentor engineers, implement testing and monitoring, manage data warehouses/lakes, and collaborate cross-functionally to deliver robust data infrastructure that supports ML and product teams.

Define and lead the technical architecture for a lakehouse on AWS, build production pipelines and data models for time-series and multi-source data, introduce data governance and catalog foundations, author platform playbooks (ADRs, runbooks, Terraform modules), deliver projects end-to-end, and mentor engineers while representing the platform to senior leadership and non-technical stakeholders.

Lead enterprise insurance analytics initiatives supporting underwriting, claims, finance, and operations. Build reporting and dashboards, ensure data integrity across TPAs and systems, support captive program performance, partner with actuary and IT, and present actionable insights to leadership.

Lead customer-facing data engineering and warehousing initiatives on the Databricks platform. Architect and optimize production-scale ETL/ELT pipelines, performance-test workloads, migrate legacy systems to cloud lakehouse architectures, support Solution Architects in technical sales, and provide training, demos, and community contributions.