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

Serve as a strategic client-facing advisor for Zeta Data Cloud solutions: demo products, support audience curation, audit accounts, identify intelligence-driven opportunities, train client teams, contribute client feedback to the product roadmap, and support RFPs to drive adoption and growth for agency partners.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & 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 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 design and optimization of high-throughput data ingestion pipelines and Python-based microservices. Drive architectural decisions, performance tuning, observability, and scalability across distributed systems. Partner with platform, data, and product teams to standardize ingestion frameworks and enable analytics-ready data in Snowflake for reporting and downstream systems.