Top Remote Data & Analytics Jobs in Denver & Boulder, CO

The Solutions Architect leads client integration of Cedar's platform, ensuring successful project delivery through client communication and technical expertise while managing complex data structures and operational workflows.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Lead and scale reporting and analytics in a fast-paced environment, managing a US and India-based team while delivering insights and resolving bottlenecks across data workflows.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Lead analytics strategy for a financial institution, ensuring compliance and driving marketing analytics through predictive modeling and team management.

Support sales intelligence by collecting, preparing, and analyzing sales and marketing data; maintain dashboards and data quality; run pipeline and win/loss analyses; translate findings into clear visualizations and reports for stakeholders.

Manage GTM analytics strategy, lead a team of analysts, define data governance, develop forecasting models, and deliver insights to drive revenue growth.

As a Data Engineer at Edmunds, you will architect and maintain data platforms for analytics and AI/ML, ensuring scalable, reliable data processing and supporting cross-functional collaboration.

Manage SoFi's enterprise TPRM platforms, optimizing workflows, delivering data analytics reports and dashboards, and enhancing risk intelligence for decision-making.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.