Top Hybrid Senior Level Data & Analytics Jobs in CO

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

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.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Design, harden, and scale Snowflake and AWS data platforms, build dimensional data models and resilient Airflow pipelines, optimize complex SQL, develop dbt semantic layers, deploy ML models in AWS, integrate AI/LLMs into workflows, and build data APIs (FastAPI/Flask) to enable enterprise analytics and operational ROI.

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.