Top Data & Analytics Jobs in CO

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Lead data engineering efforts within Technology Consulting: design data architecture and pipelines, implement AWS/Redshift and ETL solutions, support BI (QlikView/Oracle BI), coach teams, manage client relationships and SLAs, apply systems thinking to optimize outcomes and validate solutions with stakeholders.

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.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Design, build, and optimize Snowflake-based data platform: develop ELT pipelines, data models, governance, security, performance tuning, cost optimization, CI/CD, and advanced Snowflake features. Collaborate with stakeholders, mentor engineers, and deliver scalable data solutions for analytics.

Partner with U100 sales to drive small-business growth by delivering analysis, reports, dashboards, and strategic sales support. Recommend process improvements, correct operational errors, lead projects, train sales on platforms, and support renewals and financial/contract evaluations.

Build and own end-to-end compliance data pipelines and models (case, alert, entity, transaction, risk features). Ensure data quality, monitoring, lineage, and audit-ready documentation. Partner with Compliance and engineering to close upstream gaps, improve detection signal quality, and implement measurement frameworks and reporting for control effectiveness.

The Senior Customer Lifecycle Analyst leads data-driven projects focusing on customer retention, engagement, and lifetime value, leveraging advanced analytics and visualization tools to provide business insights and recommendations.

Lead automation and measurement of the AI Governance program by building self-service dashboards, tracking Time-to-Approval and throughput, analyzing trends to remove bottlenecks, producing C-suite Evidence Packs, recommending workflow improvements, and collaborating with delivery analysts to increase governance maturity and operational throughput.

Analyze transactional and operational payments data to monitor performance, detect risk and fraud, and improve collections. Build, validate, and automate daily/weekly/monthly reports and alerts, consolidate data sources, deliver insights to stakeholders, and support special analytics projects to drive operational efficiency.

The Senior Manager of Data Engineering will build a data platform, lead a team, and ensure data accessibility to support AI and business operations.

Develop and maintain data contracts, metadata standards, AI-readiness scoring pipelines, and governance/compliance tooling. Build quality monitoring, semantic layer assets, and AI-augmented development workflows. Collaborate with data owners and platform teams to onboard assets, ensure data trust, and enable AI-driven analytics.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.