Staff Data Engineer

DAT•Denver, CO

4d•$173,000 - $216,000•Hybrid

About The Position

DAT Freight & Analytics is hiring a Staff Data Engineer to provide strategic architecture and technical leadership for its modern data platform. The role leads platform design and evolution, ensuring scalability, availability, and performance, and applies advanced architectural patterns to address complex data challenges. It also establishes and communicates technical standards across tools including dbt, Airflow, Snowflake, Kafka, and traditional ETL, while partnering with senior leadership and IT leaders on strategic data initiatives. The position architects and manages enterprise-scale data platforms, establishes best practices for security, privacy, monitoring and alerting, and CI/CD, and implements advanced data modeling approaches. The Staff Data Engineer solves complex business problems, guides the full software development and technology management lifecycle, and helps foster a culture of learning, excellence, and continuous improvement across the engineering organization. DAT describes its work environment as hybrid. For Colorado-based candidates, the stated salary range is $173,000 to $216,000, plus target bonus. The company offers a competitive salary and benefits package and describes its workplace as collaborative and supportive.

Requirements

7+ years of relevant professional engineering experience.
Proven track record building and operating large-scale distributed systems.
Bachelor’s degree in Computer Science, Computer Engineering, or a related technical discipline.
Strong data engineering background with dbt, Snowflake, Kafka, and cloud-based services such as AWS S3, EMR, and Glue.
Hands-on experience with Terraform, Airflow, Tableau, MySQL, and Oracle.
Deep knowledge of professional software engineering practices across the full technology management lifecycle.
Excellent verbal and written communication skills.
Interest in continuous learning and improvement.

Nice To Haves

Experience with Agile.

Responsibilities

Lead the design and evolution of the modern data platform architecture to ensure scalability, availability, and performance.
Apply architectural patterns such as event-driven architecture, CQRS, event sourcing, and Saga patterns to solve complex data challenges.
Develop, document, and communicate standard methods and processes for the technology stack, including dbt, Airflow, Snowflake, Kafka, and traditional ETL.
Partner with senior leadership on strategic data projects and build relationships with IT leaders through technical expertise and thought leadership.
Architect and manage enterprise-scale data platforms and establish development best practices for security, privacy, monitoring and alerting, and CI/CD.
Implement sophisticated data modeling strategies, including Kimball, Inmon, or Data Vault, and drive progress toward modern concepts such as Data Mesh.
Provide solutions to complex business problems that enable better organizational decision-making.
Establish and enforce best practices throughout the software development and technology management lifecycle, including coding standards, code reviews, source control management, and testing.
Foster a culture of learning and excellence within the engineering organization.
Use data to prioritize work and influence others across the organization.
Implement changes and improvements to optimize the platform or processes.