Top Data Engineer Jobs in Denver & Boulder, CO

The Head of Machine Learning and AI will lead teams, define strategies, manage ML/AI initiatives, and foster collaboration to enhance product delivery and decision-making.

As a Senior Data Scientist, you will build models, provide mentorship, and develop techniques to optimize user experiences and drive business value.

Design and implement computer vision models for 3D dental applications, focusing on generative AI and MLOps. Collaborate with research and product teams for enhancements and ensure best practices.

As a Senior Data Engineer, you will lead data engineering projects, collaborate with teams, mentor engineers, and enhance the data infrastructure with new technologies.

As a Big Data DevOps Lead, you will improve Big Data infrastructure efficiency, lead architecture efforts, and provide on-call support for production systems.

The Director of Data Platforms and Insights at EchoStar will lead and innovate the data infrastructure and business intelligence, embedding AI capabilities for improved workflows and analytics delivery. Responsibilities include overseeing data platform innovation, AI tool development, managing project frameworks, and advocating for data governance, while mentoring teams to stay updated on industry trends.

Design and implement machine learning solutions on cloud platforms, engage with customers to define requirements, and oversee project delivery from inception to deployment.

As a Senior Data Engineer, you will build a centralized data lake on GCP, develop and optimize SPARK-powered data pipelines, and ensure data quality through validation checks. Collaborate with various teams to extract insights and maintain data models for analytics, while managing ETL/ELT processes and troubleshooting data issues.

The role involves leading a team to create innovative technology focused on artificial intelligence and natural language processing, aiming to transform digital communication.

As a Lead Data Engineer, you'll architect and maintain data pipelines, ensuring their reliability and scalability, while collaborating closely with AI and data teams.