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

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Develop and improve TransUnion's IP geolocation technology by analyzing large datasets, implementing automation algorithm improvements, and providing analytic insights. Collaborate with engineers and data scientists, use SQL/R/Python/MongoDB/BigQuery, and communicate findings to nontechnical stakeholders. Hybrid role with regular in-office work.

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 architecture and implementation of enterprise data warehousing, ETL, and master data management. Design and troubleshoot data models, deployment of data services, and end-to-end data solutions. Oversee ETL standards, mentor teams and partners, and resolve complex data engineering issues to support analytics and decision-making.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

Design, build, and maintain cloud-based data pipelines, lakes, lakehouses and warehouses for batch and real-time processing. Optimize SQL and data models, provide production support, and deliver BI applications while following Agile practices.