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

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

As a Data Engineer II, you will build, scale, and optimize data platforms, focusing on ETL/ELT pipelines, and collaborate with data scientists and AI engineers to support data-driven applications and insights.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

As a Digital Innovation Co-Op, you'll work on projects involving AI and machine learning to enhance supply chain operations, collaborating with engineers and data scientists to automate workflows and analyze data.

The role involves consulting on data-driven healthcare solutions, collaborating with teams, designing demos, and developing business strategies targeted at C-level executives in healthcare.

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

Lead a team of data and infrastructure engineers to develop cloud-based data systems and solutions for analytics, ensuring best practices in data management and MLOps.

Design, develop, integrate, test, and optimize scalable data integration solutions and pipelines for the OneGL finance environment. Support production users and month-end close processes, troubleshoot issues, develop test scripts, and document architectures. Collaborate with technical and business stakeholders, perform gap analysis, and support implementation and post-implementation activities.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

Build and maintain production-grade data models and pipelines for the Compliance Data Mart, implement data quality frameworks and monitoring, partner with engineering to resolve data gaps, support regulatory exams and audits, and automate manual workflows into scalable pipelines and self-serve tooling.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.