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

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.

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.

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 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.

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.

Lead design and optimization of high-throughput data ingestion pipelines and Python-based microservices. Improve pipeline performance, reliability, and observability across distributed systems, define unified ingestion architectures, work with Snowflake for analytics, mentor engineers, and collaborate cross-functionally to ensure scalable, fault-tolerant data platforms.